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List of Citations from Science Citation Index for
M. Kass, A. Witkin, and D. Terzopoulos, ``Snakes - Active Contour Models'' International Journal of Computer Vision, 1(4): 321-331, 1987.
1988: 2 1989: 1 1990: 1 1993: 11 1994: 25 1995: 37 1996: 74 1997: 99 1998: 88 1999: 115 2000: 129 2001: 129 2002: 134 2003: 172 2004: 194 2005: 27
Total citations: 1238
As of 11 Mar 2005
By Year - By Citation Rank - By Year with Abstract
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1988 |
1. | TERZOPOULOS, D, WITKIN, A, and KASS, M, "CONSTRAINTS ON DEFORMABLE MODELS - RECOVERING 3D SHAPE AND NONRIGID MOTION," ARTIFICIAL INTELLIGENCE, vol. 36, pp. 91-123, 1988.
Abstract:
We present a new approach to the analysis of dynamic facial
images for the purposes of estimating and resynthesizing
dynamic facial expressions. The approach exploits a
sophisticated generative model of the human face originally
developed for realistic facial animation. The face model, which
may be simulated and rendered at interactive rates on a
graphics workstation, incorporates a physics-based synthetic
facial tissue and a set of anatomically motivated facial muscle
actuators. We consider the estimation of dynamic facial muscle
contractions from video sequences of expressive human faces. We
develop an estimation technique that uses deformable contour
models (snakes) to track the nonrigid motions of facial
features in video images. The technique estimates muscle
actuator controls with sufficient accuracy to permit the face
model to resynthesize transient expressions.
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2. | TERZOPOULOS, D, and WITKIN, A, "PHYSICALLY BASED MODELS WITH RIGID AND DEFORMABLE COMPONENTS," IEEE COMPUTER GRAPHICS AND APPLICATIONS, vol. 8, pp. 41-51, 1988.
Abstract:
We present a new approach to the analysis of dynamic facial
images for the purposes of estimating and resynthesizing
dynamic facial expressions. The approach exploits a
sophisticated generative model of the human face originally
developed for realistic facial animation. The face model, which
may be simulated and rendered at interactive rates on a
graphics workstation, incorporates a physics-based synthetic
facial tissue and a set of anatomically motivated facial muscle
actuators. We consider the estimation of dynamic facial muscle
contractions from video sequences of expressive human faces. We
develop an estimation technique that uses deformable contour
models (snakes) to track the nonrigid motions of facial
features in video images. The technique estimates muscle
actuator controls with sufficient accuracy to permit the face
model to resynthesize transient expressions.
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1989 |
3. | BOOKSTEIN, FL, "PRINCIPAL WARPS - THIN-PLATE SPLINES AND THE DECOMPOSITION OF DEFORMATIONS," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 11, pp. 567-585, 1989.
Abstract:
We present a new approach to the analysis of dynamic facial
images for the purposes of estimating and resynthesizing
dynamic facial expressions. The approach exploits a
sophisticated generative model of the human face originally
developed for realistic facial animation. The face model, which
may be simulated and rendered at interactive rates on a
graphics workstation, incorporates a physics-based synthetic
facial tissue and a set of anatomically motivated facial muscle
actuators. We consider the estimation of dynamic facial muscle
contractions from video sequences of expressive human faces. We
develop an estimation technique that uses deformable contour
models (snakes) to track the nonrigid motions of facial
features in video images. The technique estimates muscle
actuator controls with sufficient accuracy to permit the face
model to resynthesize transient expressions.
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1990 |
4. | VANCLEYNENBREUGEL, J, FIERENS, F, SUETENS, P, and OOSTERLINCK, A, "DELINEATING ROAD STRUCTURES ON SATELLITE IMAGERY BY A GIS- GUIDED TECHNIQUE," PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, vol. 56, pp. 893-898, 1990.
Abstract:
We present a new approach to the analysis of dynamic facial
images for the purposes of estimating and resynthesizing
dynamic facial expressions. The approach exploits a
sophisticated generative model of the human face originally
developed for realistic facial animation. The face model, which
may be simulated and rendered at interactive rates on a
graphics workstation, incorporates a physics-based synthetic
facial tissue and a set of anatomically motivated facial muscle
actuators. We consider the estimation of dynamic facial muscle
contractions from video sequences of expressive human faces. We
develop an estimation technique that uses deformable contour
models (snakes) to track the nonrigid motions of facial
features in video images. The technique estimates muscle
actuator controls with sufficient accuracy to permit the face
model to resynthesize transient expressions.
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1993 |
5. | SHUFELT, JA, and MCKEOWN, DM, "FUSION OF MONOCULAR CUES TO DETECT MAN-MADE STRUCTURES IN AERIAL IMAGERY," CVGIP-IMAGE UNDERSTANDING, vol. 57, pp. 307-330, 1993.
Abstract:
We present a new approach to the analysis of dynamic facial
images for the purposes of estimating and resynthesizing
dynamic facial expressions. The approach exploits a
sophisticated generative model of the human face originally
developed for realistic facial animation. The face model, which
may be simulated and rendered at interactive rates on a
graphics workstation, incorporates a physics-based synthetic
facial tissue and a set of anatomically motivated facial muscle
actuators. We consider the estimation of dynamic facial muscle
contractions from video sequences of expressive human faces. We
develop an estimation technique that uses deformable contour
models (snakes) to track the nonrigid motions of facial
features in video images. The technique estimates muscle
actuator controls with sufficient accuracy to permit the face
model to resynthesize transient expressions.
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6. | TERZOPOULOS, D, and WATERS, K, "ANALYSIS AND SYNTHESIS OF FACIAL IMAGE SEQUENCES USING PHYSICAL AND ANATOMICAL MODELS," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 15, pp. 569-579, 1993.
Abstract:
We present a new approach to the analysis of dynamic facial
images for the purposes of estimating and resynthesizing
dynamic facial expressions. The approach exploits a
sophisticated generative model of the human face originally
developed for realistic facial animation. The face model, which
may be simulated and rendered at interactive rates on a
graphics workstation, incorporates a physics-based synthetic
facial tissue and a set of anatomically motivated facial muscle
actuators. We consider the estimation of dynamic facial muscle
contractions from video sequences of expressive human faces. We
develop an estimation technique that uses deformable contour
models (snakes) to track the nonrigid motions of facial
features in video images. The technique estimates muscle
actuator controls with sufficient accuracy to permit the face
model to resynthesize transient expressions.
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7. | FUKUHARA, T, and MURAKAMI, T, "3-D MOTION ESTIMATION OF HUMAN HEAD FOR MODEL-BASED IMAGE- CODING," IEE PROCEEDINGS-I COMMUNICATIONS SPEECH AND VISION, vol. 140, pp. 26-35, 1993.
Abstract:
Model-based image coding applied to interpersonal communication
achieves very low bit-rate image transmission. To accomplish
it, accurate three-dimensional (3-D) motion estimation of a
speaker is necessary. A new method of 3-D motion estimation is
presented, consisting of two steps. In the first, facial
contours and feature points of a speaker are extracted using
filtering and Snake algorithms. Five feature points on a
speaker's facial image are tracked between consecutive picture
frames, which gives 2-D motion vectors of the feature points.
Then, in the second step, the 3-D motion of a speaker's head is
estimated using a three-layered neural network model, after
training with many possible motion patterns of the human head
using an existing 3-D general shape model. Experimental results
show that our method not only achieves good results but is also
more robust than existing methods, even when the motion of an
object is rather large or complicated. Accurately estimated 3-D
motion parameters can realise image transmission at a very low
bit rate.
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8. | WHITTEN, G, "SCALE-SPACE TRACKING AND DEFORMABLE SHEET MODELS FOR COMPUTATIONAL VISION," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 15, pp. 697-706, 1993.
Abstract:
Many problems in computational vision (including stereo
correspondence, motion analysis and surface reconstruction) can
be solved effectively using a constrained optimization
approach, where smoothness is the common constraint. Moreover,
these problems can be cast in a variational form that minimizes
an energy functional. Unfortunately, standard optimization
techniques tend to find only local energy minima. Coarse to
fine scale space tracking (where energy minima at reduced
resolution are found and successively tracked to higher
resolution) has been demonstrated to find solutions of
practical value. For smoothness-constrained optimization
problems, we show that scale space tracking can be implicitly
implemented by appropriately adjusting the smoothness
constraint. A useful physical model for controlled smoothness
(deformable sheets) provides a natural framework for scale
space tracking and addressing many vision problems that can be
solved by appealing to a smoothness constraint. Deformable
sheets are characterized by a global energy functional, and the
smoothness constraint is represented by a linear internal
energy term. In analogy to physical sheets, the model sheets
are deformed by problem specific external forces and, in turn,
impose smoothness on the applied forces. We have related
deformable sheet smoothness properties to Gaussian blurring
(the common expression of scale) and used this relationship to
unify the concepts of scale and smoothness. In our formulation,
the smoothness/scale state is controlled by a single parameter
in the deformable sheet model. This single parameter control of
scale makes it possible to perform scale space tracking by
solving the differential equation that describes the trajectory
of energy minima through scale space. Further, it permits
adaptive scale step size selection based on the local
properties of scale space, which allows for much larger steps
than would be possible with the conservative step size required
by nonadaptive techniques. We show that this process is
characterized by a sparse linear system and prove that the
associated matrix is positive definite and, consequently,
nonsingular. Our analysis also provides for the determination
of scale-dependent parameters, which is useful for efficient
multiresolution processing. We have applied the deformable
sheet model described to different problems in computational
vision using real imagery with encouraging results, which are
presented here.
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9. | HOGG, DC, "SHAPE IN MACHINE VISION," IMAGE AND VISION COMPUTING, vol. 11, pp. 309-316, 1993.
Abstract:
The representation of shape in machine vision is reviewed with
emphasis on the most common types of representation and recent
developments. Both planar shape and solid shape are examined
with connections and generalizations drawn wherever possible.
Particular emphasis is placed on the importance of invariant
descriptions and on the representation of shape classes.
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10. | GAUCH, JM, and PIZER, SM, "THE INTENSITY AXIS OF SYMMETRY AND ITS APPLICATION TO IMAGE SEGMENTATION," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 15, pp. 753-770, 1993.
Abstract:
In this paper, we present a new method for describing the shape
of structures in grey-scale images, which is known as the
intensity axis of symmetry (IAS). We describe the spatial and
intensity variations of the image simultaneously rather than by
the usual two-step process of 1) using intensity properties of
the image to segment an image into regions and 2) describing
the spatial shape of these regions. The result is an image
shape description that is useful for a number of computer
vision applications. Our method for computing this image shape
description relies on minimizing an active surface functional
that provides coherence in both the spatial and intensity
dimensions while deforming into an axis of symmetry. Shape-
based image segmentation is possible by identifying image
regions associated with individual components of the IAS. The
resulting image regions have geometric coherence and correspond
well to visually meaningful objects in medical images.
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11. | TSAI, CT, SUN, YN, CHUNG, PC, and LEE, JS, "ENDOCARDIAL BOUNDARY DETECTION USING A NEURAL-NETWORK," PATTERN RECOGNITION, vol. 26, pp. 1057-1068, 1993.
Abstract:
Echocardiography has been widely used as a real-time non-
invasive clinical tool to diagnose cardiac functions. Due to
the poor quality and inherent ambiguity in echocardiograms, it
is difficult to detect the myocardial boundaries of the left
ventricle. Many existing methods are semi-automatic and detect
cardial boundaries by serial computation which is too slow to
be practical in real applications. In this paper, a new method
for detecting the endocardial boundary by using a Hopfield
neural network is proposed. Taking advantage of parallel
computation and energy convergence capability in the Hopfield
network, this method is faster and more stable for the
detection of the endocardial border. Moreover, neither manual
operations nor a priori assumptions are needed in this method.
Experiments on several LV echocardiograms and clinical
validation have shown the effectiveness of our method in these
patient studies.
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12. | LINDEBERG, T, "DETECTING SALIENT BLOB-LIKE IMAGE STRUCTURES AND THEIR SCALES WITH A SCALE-SPACE PRIMAL SKETCH - A METHOD FOR FOCUS-OF- ATTENTION," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 11, pp. 283-318, 1993.
Abstract:
This article presents: (i) a multiscale representation of grey-
level shape called the scale-space primal sketch, which makes
explicit both features in scale-space and the relations between
structures at different scales, (ii) a methodology for
extracting significant blob-like image structures from this
representation, and (iii) applications to edge detection,
histogram analysis, and junction classification demonstrating
how the proposed method can be used for guiding later-stage
visual processes. The representation gives a qualitative
description of image structure, which allows for detection of
stable scales and associated regions of interest in a solely
bottom-up data-driven way. In other words, it generates coarse
segmentation cues, and can hence be seen as preceding further
processing, which can then be properly tuned. It is argued that
once such information is available, many other processing tasks
can become much simpler. Experiments on real imagery
demonstrate that the proposed theory gives intuitive results.
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13. | COHEN, LD, and COHEN, I, "FINITE-ELEMENT METHODS FOR ACTIVE CONTOUR MODELS AND BALLOONS FOR 2-D AND 3-D IMAGES," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 15, pp. 1131-1147, 1993.
Abstract:
The use of energy-minimizing curves, known as ''snakes'' to
extract features of interest in images has been introduced by
Kass, Witkin and Terzopoulos [23]. A balloon model was
introduced in [12] as a way to generalize and solve some of the
problems encountered with the original method. A 3-D
generalization of the balloon model as a 3-D deformable
surface, which evolves in 3-D images, is presented. It is
deformed under the action of internal and external forces
attracting the surface toward detected edgels by means of an
attraction potential. We also show properties of energy-
minimizing surfaces concerning their relationship with 3-D edge
points. To solve the minimization problem for a surface, two
simplified approaches are shown first, defining a 3-D surface
as a series of 2-D planar curves. Then, after comparing finite-
element method and finite-difference method in the 2-D problem,
we solve the 3-D model using the finite-element method yielding
greater stability and faster convergence. This model is applied
for segmenting magnetic resonance images.
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14. | TSAI, CT, SUN, YN, and CHUNG, PC, "MINIMIZING THE ENERGY OF ACTIVE CONTOUR MODEL USING A HOPFIELD NETWORK," IEE PROCEEDINGS-E COMPUTERS AND DIGITAL TECHNIQUES, vol. 140, pp. 297-303, 1993.
Abstract:
Active contour models (snakes) are commonly used for locating the
boundary of an object in computer vision applications. The minimisation
procedure is the key problem to solve in the technique of active
contour models. In this paper, a minimisation method for an active
contour model using Hopfield networks is proposed. Due to its network
structure, it lends itself admirably to parallel implementation and is
potentially faster than conventional methods. In addition, it retains
the stability of the snake model and the possibility for inclusion of
hard constraints. Experimental results are given to demonstrate the
feasibility of the proposed method in applications of industrial
pattern recognition and medical image processing.
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15. | WOLBERG, WH, STREET, WN, and MANGASARIAN, OL, "BREAST CYTOLOGY DIAGNOSIS WITH DIGITAL IMAGE-ANALYSIS," ANALYTICAL AND QUANTITATIVE CYTOLOGY AND HISTOLOGY, vol. 15, pp. 396-404, 1993.
Abstract:
An interactive computer system has been developed for evaluating
cytologic features derived directly from a digital scan of breast fine
needle aspirate slides. The system uses computer vision techniques to
analyze cell nuclei and classifies them using an inductive method based
on linear programming. A digital scan of selected areas of the aspirate
slide is done by a trained observer, while the analysis of the
digitized image is done by an untrained observer. When trained and
tested on 119 breast fine needle aspirates (68 benign and 51 malignant)
using leave-one-out testing, 90% correctness was achieved. These
results indicate that the method is accurate (good intraobserver and
interobserver reproducibility) and that an untrained operator can
obtain diagnostic results comparable to those achieved visually by
experienced observers.
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1994 |
16. | CANNING, J, "A MINIMUM DESCRIPTION LENGTH MODEL FOR RECOGNIZING OBJECTS WITH VARIABLE APPEARANCES (THE VAPOR MODEL)," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 16, pp. 1032-1036, 1994.
Abstract:
Most object recognition systems can only model objects composed of
rigid pieces whose appearance depends only on lighting and viewpoint.
Many real world objects, however, have variable appearances because
they are flexible and/or have a variable number of parts. These
objects cannot be easily modeled using current techniques. We propose
the use of a knowledge representation called the VAPOR (Variable
APpearance Object Representation) model to represent objects with these
kinds of variable appearances. The VAPOR model is an idealization of
the object; all instances of the model in an image are variations from
the ideal appearance. The variations are evaluated by the description
length of the data given the model, i.e., the number of
information-theoretic bits needed to represent the model and the
deviations of the data from the ideal appearance. The shortest length
model is chosen as the best description. We demonstrate how the VAPOR
model performs in a simple domain of circles and polygons and in the
complex domain of finding cloverleaf interchanges in aerial images of
roads.
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17. | STORVIK, G, "A BAYESIAN-APPROACH TO DYNAMIC CONTOURS THROUGH STOCHASTIC SAMPLING AND SIMULATED ANNEALING," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 16, pp. 976-986, 1994.
Abstract:
In many applications of image analysis, simply connected objects are to
be located in noisy images. During the last 5-6 years active contour
models have become popular for finding the contours of such objects.
Connected to these models are iterative algorithms for finding the
minimizing energy curves making the curves behave dynamically through
the iterations. These approaches do however have several
disadvantages. The numerical algorithms that are in use constraint the
models that can be used. Furthermore, in many cases only local minima
can be achieved.
In this paper, we discuss a method for curve detection based on a fully
Bayesian approach. A model for image contours which allows the number
of nodes on the contours to vary is introduced. Iterative algorithms
based on stochastic sampling is constructed, which make it possible to
simulate samples from the posterior distribution, making estimates and
uncertainty measures of specific quantities available. Further,
simulated annealing schemes making the curve move dynamically towards
the global minimum energy configuration are presented. In theory, no
restrictions on the models are made. In practice, however,
computational aspects must be taken into consideration when choosing
the models. Much more general models than the one used for active
contours may however be applied.
The approach is applied to ultrasound images of the left ventricle and
to Magnetic Resonance images of the human brain, and show promising
results.
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18. | MOSHFEGHI, M, RANGANATH, S, and NAWYN, K, "3-DIMENSIONAL ELASTIC MATCHING OF VOLUMES," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 3, pp. 128-138, 1994.
Abstract:
Registering volumes that have been deformed with respect to each other
involves recovery of the deformation. A 3-D elastic matching algorithm
has been developed to use surface information for registering volumes.
Surface extraction is performed in two steps: extraction of contours in
2-D image planes using active contours, and forming triangular patch
surface models from the stack of 2-D contours. One volume is modeled as
being deformed with respect to another goal volume. Correspondences
between surfaces in the two image volumes are used to warp the deformed
volume towards its goal. This process of contour extraction, surface
formation and matching, and warping is repeated a number of times, with
decreasing image volume stiffness. As the iterations continue the
stretched volume is refined towards its goal volume. Registration
examples of deformed volumes are presented.
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19. | WANG, Y, and LEE, O, "ACTIVE MESH - A FEATURE SEEKING AND TRACKING IMAGE SEQUENCE REPRESENTATION SCHEME," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 3, pp. 610-624, 1994.
Abstract:
This paper introduces a representation scheme for image sequences using
nonuniform samples embedded in a deformable mesh structure. It
describes a sequence by nodal positions and colors in a starting frame,
followed by nodal displacements in the following frames. The nodal
points in the mesh are more densely distributed in regions containing
interesting features such as edges and corners; and are dynamically
updated to follow the same features in successive frames. They are
determined automatically by maximizing feature (e.g, gradient)
magnitudes at nodal points, while minimizing interpolation errors
within individual elements, and matching errors between corresponding
elements. In order to avoid the mesh elements becoming overly deformed,
a penalty term is also incorporated, which measures the irregularity of
the mesh structure. The notions of shape functions and master elements
commonly used in the finite element method have been applied to
simplify the numerical calculation of the energy functions and their
gradients. The proposed representation is motivated by the active
contour or snake model proposed by Kass, Witkin, and Terzopoulos. The
current representation retains the salient merit of the original model
as a feature tracker based on local and collective information, while
facilitating more accurate image interpolation and prediction. Our
computer simulations have shown that the proposed scheme can
successfully track facial feature movements in head-and-shoulder type
of sequences, and more generally, interframe changes that can be
modeled as elastic deformation. The treatment for the starting frame
also constitutes an efficient representation of arbitrary still images.
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20. | RUAN, S, BRUNO, A, and COATRIEUX, JL, "3-DIMENSIONAL MOTION AND RECONSTRUCTION OF CORONARY-ARTERIES FROM BIPLANE CINEANGIOGRAPHY," IMAGE AND VISION COMPUTING, vol. 12, pp. 683-689, 1994.
Abstract:
A new approach is described for reconstructing coronary arteries from
two sequences of projection images. The estimation of motion is
performed on three-dimensional line segments (or centrelines), and is
based on a 'prediction-projection-optimization' loop. The method copes
with time varying properties, deformations and superpositions of
vessels. Experiments using simulated and real data have been carried
out, and the results found to be robust over a full cycle of a human
heart. Local and global kinetic features can then be derived to obtain
a greater insight on the cardiac functional state
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21. | DING, K, and GUNASEKARAN, S, "SHAPE FEATURE-EXTRACTION AND CLASSIFICATION OF FOOD MATERIAL USING COMPUTER VISION," TRANSACTIONS OF THE ASAE, vol. 37, pp. 1537-1545, 1994.
Abstract:
Food material shape is often closely related to its qualify. Due to the
demands of high quality, automated food shape inspection has become an
important need for the food industry. Currently, accuracy and speed are
two major problems for food shape inspection with computer vision.
Therefore, in this study, a fast and accurate computer-vision based
feature extraction and classification system was developed. In the
feature extraction stage, a statistical model based feature extractor
(SMB) and a multi-index active model-based (MAM) feature extractor were
developed to improve the accuracy of classifications. In the
classification stage, first the back-propagation neural network was
applied as a multi-index classifier. Then, to speed up training, some
minimum indeterminate zone (MIZ) classifiers were developed. Corn
kernels, almonds, and animal-shaped crackers were used to rest the
above techniques. The results showed that accuracy and speed were
greatly improved when the MAM feature extractor was used in conjunction
with the MIZ classifier.
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22. | XU, G, SEGAWA, E, and TSUJI, S, "ROBUST ACTIVE CONTOURS WITH INSENSITIVE PARAMETERS," PATTERN RECOGNITION, vol. 27, pp. 879-884, 1994.
Abstract:
Active contours, known as snakes, have found wide applications since
their first introduction in 1987 by Kass et al. (Int. J. Comput. Vision
1, 321-331). However, one problem with the current models is that the
performance depends on proper internal parameters and initial contour
position, which, unfortunately, cannot be determined a priori. It is
usually a hard job to tune internal parameters and initial contour
position. The problem comes from the fact that the internal normal
force at each point of contour is also a function of contour shape. To
solve this problem, we propose to compensate for this internal normal
force so as to make it independent of shape. As a result, the new model
works robustly with no necessity to fine-tune internal parameters, and
can converge to high curvature points like corners.
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23. | CARLBOM, I, TERZOPOULOS, D, and HARRIS, KM, "COMPUTER-ASSISTED REGISTRATION, SEGMENTATION, AND 3D RECONSTRUCTION FROM IMAGES OF NEURONAL TISSUE-SECTIONS," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 13, pp. 351-362, 1994.
Abstract:
Neuroscientists have studied the relationship between nerve cell
morphology and function for over a century. To pursue these studies,
they need accurate three-dimensional models of nerve cells that
facilitate detailed anatomical measurement and the identification of
internal structures. Although serial transmission electron microscopy
has been a source of such models since the mid 1960s, model
reconstruction and analysis remain very time consuming. We have
developed a new approach to reconstructing and visualizing 3D nerve
cell models from serial microscopy. An interactive system exploits
recent computer graphics and computer vision techniques to
significantly reduce the time required to build such models. The key
ingredients of the system are a digital ''blink comparator'' for
section registration, ''snakes,'' or active deformable contours, for
semiautomated cell segmentation, and voxel-based techniques for 3D
reconstruction and visualization of complex cell volumes with internal
structures.
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24. | THIRION, JP, "DIRECT EXTRACTION OF BOUNDARIES FROM COMPUTED-TOMOGRAPHY SCANS," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 13, pp. 322-328, 1994.
Abstract:
This paper presents a method, based on the Filtered Backprojection
technique (FBP), to extract directly the boundaries of X-ray images,
without previous image reconstruction. We preprocess the raw data in
order to compute directly the reconstructed values of the gradient or
of the Laplacian at any location in the plane (defined with real
coordinates). The reconstructed value of the gradient and of the
Laplacian correspond to the exact mathematical definition of the
differentials of the image. For noisy data, we propose also to use an
extension of existing FBP techniques, adapted to the computation of the
gradient and of the Laplacian. Finally, we show how to use the
corresponding operators to perform the segmentation of a slice, without
image reconstruction. Images of the reconstructed gradient, Laplacian,
and segmented objects are presented.
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25. | DAYANAND, S, UTTAL, WR, SHEPHERD, T, and LUNSKIS, C, "A PARTICLE SYSTEM MODEL FOR COMBINING EDGE INFORMATION FROM MULTIPLE SEGMENTATION MODULES," CVGIP-GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 56, pp. 219-230, 1994.
Abstract:
A model for fusing the output of multiple segmentation modules is
presented. The model is based on the particle system approach to
modeling dynamic objects from computer graphics. The model also has
built-in capabilities to extract regions, thin the edge image, remove
''twigs,'' and close gaps in the contours. The model functions both as
an effective data fusion technique and as a model of an important human
visual process. (C) 1994 Academic Press, Inc.
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26. | MANHAEGHE, C, LEMAHIEU, I, VOGELAERS, D, and COLARDYN, F, "AUTOMATIC INITIAL ESTIMATION OF THE LEFT-VENTRICULAR MYOCARDIAL MIDWALL IN EMISSION TOMOGRAMS USING KOHONEN MAPS," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 16, pp. 259-266, 1994.
Abstract:
A new method to make an automatic initial estimation of the position of
the middle of the left ventricular (LV) myocardial wall (LV myocardial
midwall) in emission tomograms is presented. This method eliminates the
manual interaction still required by other, more accurate LV
delineation algorithms, and which consists of indicating the LV long
axis and/or the LV extremities. A well-known algorithm from the world
of neural networks, Kohonen's self-organizing maps, was adapted to use
general shapes and to behave well for data with large background noise.
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27. | RONFARD, R, "REGION-BASED STRATEGIES FOR ACTIVE CONTOUR MODELS," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 13, pp. 229-251, 1994.
Abstract:
The variational method has been introduced by Kass et al. (1987) in the
field of object contour modeling, as an alternative to the more
traditional edge detection-edge thinning-edge sorting sequence. Since
the method is based on a pre-processing of the image to yield an edge
map, it shares the limitations of the edge detectors it uses. In this
paper, we propose a modified variational scheme for contour modeling,
which uses no edge detection step, but local computations instead-only
around contour neighborhoods-as well as an ''anticipating'' strategy
that enhances the modeling activity of deformable contour curves. Many
of the concepts used were originally introduced to study the local
structure of discontinuity, in a theoretical and formal statement by
Leclerc & Zucker (1987), but never in a practical situation such as
this one. The first part of the paper introduces a region-based energy
criterion for active contours, and gives an examination of its
implications, as compared to the gradient edge map energy of snakes.
Then, a simplified optimization scheme is presented, accounting for
internal and external energy in separate steps. This leads to a
complete treatment, which is described in the last sections of the
paper (4 and 5). The optimization technique used here is mostly
heuristic, and is thus presented without a formal proof, but is
believed to fill a gap between snakes and other useful image
representations, such as split-and-merge regions or mixed line-labels
image fields.
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28. | CHEN, LH, LIN, WC, and LIAO, HYM, "RECOVERY OF SUPERQUADRIC PRIMITIVE FROM STEREO IMAGES," IMAGE AND VISION COMPUTING, vol. 12, pp. 285-295, 1994.
Abstract:
This paper presents an integrated approach to recovering the
superquadric primitive from stereo images. While the depth data
obtained from stereo matching algorithms are always sparse and noisy,
to extract an object from the scene and obtain a smoothed depth map of
the object, occluding contour detection and surface reconstruction are
incorporated into the recovery process of superquadrics. The algorithm
combines the recovery processes of occluding contour, surface and
volumetric models in a cooperative and synergetic manner. The
performance of the algorithm is demonstrated with two examples using
real images.
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29. | YOUNG, AA, IMAI, H, CHANG, CN, and AXEL, L, "2-DIMENSIONAL LEFT-VENTRICULAR DEFORMATION DURING SYSTOLE USING MAGNETIC-RESONANCE-IMAGING WITH SPATIAL MODULATION OF MAGNETIZATION," CIRCULATION, vol. 89, pp. 740-752, 1994.
Abstract:
Background Myocardial tissue tagging with the use of magnetic resonance
imaging allows noninvasive regional analysis of heart wall motion and
deformation. However, any evaluation of the effect of disease or
treatment requires a baseline reference of normal values and variation.
We studied the two-dimensional motion of material points imaged within
the left ventricular wall using spatial modulation of magnetization
(SPAMM) in 12 normal human volunteers. Methods and Results Five
parallel short-axis and five parallel long-axis slices were acquired at
five times during systole. SPAMM tags were generated at end diastole
using a 7-mm grid. Intersection point data were analyzed for
displacement, rotation, and torsion, and triangles of points were
analyzed for local rotation and principal strains. Short-axis
displacement was the least in the septum for all longitudinal levels
(P<.001). Torsion about the long axis was uniform circumferentially
because of the motion of the centroids used to reference the rotation.
In the long-axis images, the base displaced longitudinally toward the
apex, with the posterior wall moving farther than the anterior wall
(13.4+/-2.2 versus 9.7+/-1.8 mm, P<.001) in this direction. The largest
principal strain (maximum lengthening) was approximately radially
oriented in both views. In the short-axis images, the minimum principal
strain (maximum shortening) increased in magnitude toward the apex
(P<.001) with little circumferential variation, except at midventricle,
where the anterior wall showed greater contraction than the posterior
wall (-0.21+/-0.03 versus -0.19+/-0.02, P<.02). Conclusions Consistent
regional variations in deformation are seen in the normal human heart,
Displacement and maximum shortening strains are well characterized with
two-dimensional magnetic resonance tagging; however, higher-resolution
images will be required to study transmural variations.
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30. | KOEPFLER, G, LOPEZ, C, and MOREL, JM, "A MULTISCALE ALGORITHM FOR IMAGE SEGMENTATION BY VARIATIONAL METHOD," SIAM JOURNAL ON NUMERICAL ANALYSIS, vol. 31, pp. 282-299, 1994.
Abstract:
Most segmentation algorithms are composed of several procedures: split
and merge, small region elimination, boundary smoothing,..., each
depending on several parameters. The introduction of an energy to
minimize leads to a drastic reduction of these parameters. The authors
prove that the most simple segmentation tool, the ''region merging''
algorithm, made according to the simplest energy, is enough to compute
a local energy minimum belonging to a compact class and to achieve the
job of most of the tools mentioned above. The authors explain why
''merging'' in a variational framework leads to a fast multiscale,
multichannel algorithm, with a pyramidal structure. The obtained
algorithm is O(n ln n), where n is the number of pixels of the picture.
This fast algorithm is applied to make grey level and texture
segmentation and experimental results are shown.
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31. | CALWAY, AD, and WILSON, R, "CURVE EXTRACTION IN IMAGES USING A MULTIRESOLUTION FRAMEWORK," CVGIP-IMAGE UNDERSTANDING, vol. 59, pp. 359-366, 1994.
Abstract:
A multiresolution approach to curve extraction in images is described.
Based on a piecewise linear representation of curves, the scheme
combines an efficient method of extracting line segments with a
grouping process to identify curve traces. The line segments correspond
to linear features defined at appropriate spatial resolutions within a
quadtree structure and are extracted using a hierarchical decision
process based on frequency domain properties. Implementation is
achieved through the use of the multiresolution Fourier transform, a
linear transform providing spatially localized estimates of the
frequency spectrum over multiple scales. The scheme is simple to
implement and computationally inexpensive, and results of experiments
performed on natural images demonstrate that its performance compares
favorably with that of existing methods. (C) 1994 Academic Press, Inc.
|
32. | NELSON, RC, "FINDING LINE SEGMENTS BY STICK GROWING," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 16, pp. 519-523, 1994.
Abstract:
A method is described for extracting lineal features from an image
using extended local information to provide robustness and sensitivity.
The method utilizes both gradient magnitude and direction information,
and incorporates explicit lineal and end-stop terms. These terms are
combined nonlinearly to produce an energy landscape in which local
minima correspond to lineal features called sticks that can be
represented as line segments. A hill climbing (stick-growing) process
is used to find these minima. The method is compared to two others, and
found to have improved gap-crossing characteristics.
|
33. | OSULLIVAN, F, and QIAN, MJ, "A REGULARIZED CONTRAST STATISTIC FOR OBJECT BOUNDARY ESTIMATION - IMPLEMENTATION AND STATISTICAL EVALUATION," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 16, pp. 561-570, 1994.
Abstract:
We propose an optimization approach to the estimation of a simple
closed curve describing the boundary of an object represented in an
image. The problem arises in a variety of applications, such as
template matching schemes for medical image registration. A regularized
optimization formulation with an objective function that measures the
normalized image contrast between the inside and outside of a boundary
is proposed. Numerical methods are developed to implement the approach,
and a set of simulation studies are carried out to quantify statistical
performance characteristics. One set of simulations models emission
computed tomography (ECT) images; a second set considers images with a
locally coherent noise pattern. In both cases, the error
characteristics are found to be quite encouraging. The approach is
highly automated, which offers some practical advantages over currently
used technologies in the medical imaging field.
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34. | KUMAR, S, and GOLDGOF, D, "AUTOMATIC TRACKING OF SPAMM GRID AND THE ESTIMATION OF DEFORMATION PARAMETERS FROM CARDIAC MR-IMAGES," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 13, pp. 122-132, 1994.
Abstract:
In this paper, we present a new approach for the automatic tracking of
SPAMM (Spatial Modulation of Magnetization) grid in cardiac MR images
and consequent estimation of deformation parameters. The tracking is
utilized to extract grid points from MR images and to establish
correspondences between grid points in images taken at consecutive
frames. These correspondences are used with a thin plate spline model
to establish a mapping from one image to the next. This mapping is then
used for motion and deformation estimation. Spatio-temporal tracking of
SPAMM grid is achieved by using snakes-active contour models with an
associated energy functional. We present a minimizing strategy which is
suitable for tracking the SPAMM grid. By continuously minimizing their
energy functionals, the snakes lock on to and follow the in-slice
motion and deformation of the SPAMM grid. The proposed algorithm was
tested with excellent results on 123 images (three data sets each a
multiple slice 2D, 16 phase Cine study, three data sets each a multiple
slice 2D, 13 phase Cine study and three data sets each a multiple slice
2D, 12 phase Cine study).
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35. | RAPPOPORT, A, HELOR, Y, and WERMAN, M, "INTERACTIVE DESIGN OF SMOOTH OBJECTS WITH PROBABILISTIC POINT CONSTRAINTS," ACM TRANSACTIONS ON GRAPHICS, vol. 13, pp. 156-176, 1994.
Abstract:
Point displacement constraints constitute an attractive technique for
interactive design of smooth curves, surfaces, and volumes. The user
defines an arbitrary number of ''control points'' on the object and
specifies their desired spatial location, while the system computes the
object's degrees of freedom so that the constraints are satisfied. A
constraint-based interface gives a feeling of direct manipulation of
the object. In this article we introduce soft constraints, constraints
which do not have to be met exactly. The softness of each constraint
serves as a nonisotropic, local shape parameter enabling the user to
explore the space of objects conforming to the constraints.
Additionally, there is a global shape parameter which determines the
amount of similarity of the designed object to a rest shape, or
equivalently, the rigidity of the rest shape.
We present an algorithm termed probabilistic point constraints (PPC)
for implementing soft constraints. The PPC algorithm views constraints
as stochastic measurements of the state of a static system. The
softness of a constraint is derived from the covariance of the
''measurement.'' The resulting system of probabilistic equations is
solved using the Kalman filter, a powerful estimation tool in the
theory of stochastic systems. We also describe a user interface using
direct-manipulation devices for specifying and visualizing covariances
in 2D and 3D.
The algorithm is suitable for any object represented as a parametric
blend of control points, including most spline representations. The
covariance of a constraint provides a continuous transition from exact
interpolation to controlled approximation of the constraint. The
algorithm involves only linear operations and allows real-time
interactive direct manipulation of curves and surfaces on current
workstations.
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36. | GUNASEKARAN, S, and DING, KX, "USING COMPUTER VISION FOR FOOD QUALITY EVALUATION," FOOD TECHNOLOGY, vol. 48, pp. 151-154, 1994.
Abstract:
Image warping, often referred to as ''rubber sheeting,'' represents the
deformation of a domain image space into a range image space. In this
paper, a technique which extends the definition of a rubber-sheet
transformation to allow a polygonal region to be warped into one or
more subsets of itself, where the subsets may be multiply connected, is
described. To do this, it constructs a set of ''slits'' in the domain
image, which correspond to discontinuities and concavities in the range
image, using a technique based on generalized Voronoi diagrams. The
concept of medial axis is extended to describe inner and outer medial
contours of a polygon. Polygonal regions are decomposed into annular
subregions, and path homotopies are introduced to describe the annular
subregions. These constructions motivate the definition of a ladder,
which guides the construction of grid point pairs necessary to effect
the warp itself. (C) 1994 Academic Press, Inc.
|
37. | LANDAU, P, and SCHWARTZ, E, "SUBSET WARPING - RUBBER SHEETING WITH CUTS," CVGIP-GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 56, pp. 247-266, 1994.
Abstract:
Image warping, often referred to as ''rubber sheeting,'' represents the
deformation of a domain image space into a range image space. In this
paper, a technique which extends the definition of a rubber-sheet
transformation to allow a polygonal region to be warped into one or
more subsets of itself, where the subsets may be multiply connected, is
described. To do this, it constructs a set of ''slits'' in the domain
image, which correspond to discontinuities and concavities in the range
image, using a technique based on generalized Voronoi diagrams. The
concept of medial axis is extended to describe inner and outer medial
contours of a polygon. Polygonal regions are decomposed into annular
subregions, and path homotopies are introduced to describe the annular
subregions. These constructions motivate the definition of a ladder,
which guides the construction of grid point pairs necessary to effect
the warp itself. (C) 1994 Academic Press, Inc.
|
38. | WEISS, I, "HIGH-ORDER DIFFERENTIATION FILTERS THAT WORK," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 16, pp. 734-739, 1994.
Abstract:
Reliable derivatives or digital images have always been hard to obtain,
especially (but not only) at high orders. We analyze the sources of
errors in traditional filters, such as derivatives or the Gaussian,
that are used for differentiation. We then study a class of filters
which is much more suitable for our purpose, namely filters that
preserve polynomials up to a given order. We show that the errors in
differentiation can be corrected using these filters. We derive a
condition for the validity domain of these filters, involving some
characteristics of the filter and of the shape. Our experiments show a
very good performance for smooth functions.
|
39. | YOUNG, AA, KRAMER, CM, FERRARI, VA, AXEL, L, and REICHEK, N, "3-DIMENSIONAL LEFT-VENTRICULAR DEFORMATION IN HYPERTROPHIC CARDIOMYOPATHY," CIRCULATION, vol. 90, pp. 854-867, 1994.
Abstract:
Background In hypertrophic cardiomyopathy, ejection fraction is normal
or increased, and force-length relations are reduced. However,
three-dimensional (3D) motion and deformation in vivo have not been
assessed in this condition. We have reconstructed the 3D motion of the
left ventricle (LV) during systole in 7 patients with hypertrophic
cardiomyopathy (HCM) and 12 normal volunteers by use of magnetic
resonance tagging.
Methods and Results Transmural tagging stripes were automatically
tracked to subpixel resolution with an active contour model. A 3D
finite-element model was used to interpolate displacement information
between short- and long-axis slices and register data on a regional
basis. Displacement and strain data were averaged into septal,
posterior, lateral, and anterior regions at basal, midventricular, and
apical levels. Radial motion (toward the central long axis) decreased
slightly in patients with HCM, whereas longitudinal displacement
(parallel to the long axis) of the base toward the apex was markedly
reduced: 7.5 +/- 2.5 mm (SD) versus 12.5 +/- 2.0 mm, P<.001.
Circumferential and longitudinal shortening were both reduced in the
septum (P<.01 at all levels). The principal strain associated with 3D
maximal contraction was slightly depressed in many regions,
significantly in the basal septum (-0.18 +/- 0.05 versus -0.22 +/-
0.02, P<.05) walls. In contrast, LV torsion (twist of the apex about
the long axis relative to the base) was greater in HCM patients (19.9
+/- 2.4 degrees versus 14.6 +/- 2.7 degrees, P<.01).
Conclusions HCM patients had reduced 3D myocardial shortening on a
regional basis; however, LV torsion was increased.
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40. | FUJIMURA, K, YOKOYA, N, and YAMAMOTO, K, "MOTION ANALYSIS OF NONRIGID OBJECTS BY ACTIVE CONTOUR MODELS USING MULTISCALE IMAGES," SYSTEMS AND COMPUTERS IN JAPAN, vol. 25, pp. 81-91, 1994.
Abstract:
This paper considers the approach to dynamic image processing, which is
one of the important problems in the future medical image processing.
The tracking of the object and the analysis of the motion are discussed
for the dynamic images of a nonrigid object with smooth shape, motion
and deformation, which is the case in most medical images. This
approach is based on an active contour model defined by an energy
function in terms of both intra- and interframe constraints for the
contour of the object. The contour of the target object is extracted
and tracked by minimizing the energy function using multiscale dynamic
programming and the motion is analyzed.
The dynamic programming in multiscale proposed in this paper is to
adjust the search neighborhood of the dynamic programming according to
the scale. The coarse or fine neighborhood is defined for the coarse
and fine scales, respectively, and the energy is minimized starting
from the coarse scale and shifting to the fine scale. By this scheme, a
large motion an deformation of the object can be handled.
The proposed motion tracking method has been applied successfully to
the dynamic image in the ''behavioral analysis of a slug aiming at the
analysis of the neural mechanism of learning and memory formation in
slugs,'' as well as to dynamic echocardiographic images.
In the first application, the positive maximum of the curvature along
the contour is extracted in the motion analysis as a characteristic
point invariant to the deformation of the object. Then the shift of
that point is traced. By this approach, the rough motion of the object
can be estimated.
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1995 |
41. | UEDA, N, and MASE, K, "TRACKING MOVING CONTOURS USING ENERGY-MINIMIZING ELASTIC CONTOUR MODELS," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 9, pp. 465-484, 1995.
Abstract:
This paper proposes a robust method for tracking an object contour in a
sequence of images. In this method, both object extraction and tracking
problems can be solved simultaneously. Furthermore, it is applicable to
the tracking of arbitrary shapes since it does not need a priori
knowledge about the object shapes. In the contour tracking,
energy-minimizing elastic contour models are utilized, which is newly
presented in this paper. The contour tracking is formulated as an
optimization problem to find the position that minimizes both the
elastic energy of its model and the potential energy derived from the
edge potential image that includes a target object contour. We also
present an algorithm which efficiently solves energy minimization
problems within a dynamic programming framework. The algorithm enables
us to obtain optimal solution even when the variables to be optimized
are not ordered. We show the validity and usefulness of the proposed
method with some experimental results.
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42. | FUA, P, and LECLERC, YG, "OBJECT-CENTERED SURFACE RECONSTRUCTION - COMBINING MULTIIMAGE STEREO AND SHADING," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 16, pp. 35-56, 1995.
Abstract:
Our goal is to reconstruct both the shape and reflectance properties of
surfaces from multiple images. We argue that an object-centered
representation is most appropriate for this purpose because it
naturally accommodates multiple sources of data, multiple images
(including motion sequences of a rigid object), and self-occlusions. We
then present a specific object-centered reconstruction method and its
implementation. The method begins with an initial estimate of surface
shape provided, for example, by triangulating the result of
conventional stereo. The surface shape and reflectance properties are
then iteratively adjusted to minimize an objective function that
combines information from multiple input images. The objective function
is a weighted sum of stereo, shading, and smoothness components, where
the weight varies over the surface. For example, the stereo component
is weighted more strongly where the surface projects onto highly
textured areas in the images, and less strongly otherwise. Thus, each
component has its greatest influence where its accuracy is likely to be
greatest. Experimental results on both synthetic and real images are
presented.
|
43. | BITTAR, E, TSINGOS, N, and GASCUEL, MP, "AUTOMATIC RECONSTRUCTION OF UNSTRUCTURED 3D DATA - COMBINING A MEDIAL AXIS AND IMPLICIT SURFACES," COMPUTER GRAPHICS FORUM, vol. 14, pp. C457-C468, 1995.
Abstract:
This paper presents a new method that combines a medial axis and
implicit surfaces in order to reconstruct a 3D solid from on
unstructured set of points scattered on the object's surface. The
representation produced is based on iso-surfaces generated by
skeletons, and is a particularly compact way of defining a smooth
free-form solid. The method is based on the minimisation of an energy
representing a ''distance'' between the set of data points and the
iso-surface, resembling previous reserach(19). Initialisation, however,
is more robust and efficient since there is computation of the medial
axis of the set of points. Instead of subdividing existing skeletons in
order to refine the object's surface, a new reconstruction algorithm
progressively selects skeleton-points from the precomputed medial axis
using an heuristic principle based on a ''local energy'' criterion.
This drastically speeds up the reconstruction process. Moreover, using
the medial axis allows reconstruction of objects with complex topology
and geometry, like objects that have holes and branches or that are
composed of several connected components. This process is fully
automatic. The method has been successfully applied to both synthetic
and real data.
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44. | VELTKAMP, RC, and WESSELINK, W, "MODELING 3D CURVES OF MINIMAL ENERGY," COMPUTER GRAPHICS FORUM, vol. 14, pp. C97-C110, 1995.
Abstract:
Modeling a curve through minimizing its energy yields an overall smooth
curve. A common way to model shape features is to perform the
minimization subject to a number of interpolation constraints. This way
of modeling is attractive because the designer is not bothered with the
precise representation of the curve (e.g, control points). However,
local shape specification by means of interpolation constraints is very
limited. On the other hand, local deformation by repositioning control
points is powerful but very laborious, and destroys the minimal energy
property. In this paper, deform operators are introduced for 3D curve
modeling that have built-in energy terms that have an intuitive effect.
These operators allow local shape modification and do justice to the
energy minimization way of modeling.
|
45. | BUCK, TD, EHRICKE, HH, STRASSER, W, and THURFJELL, L, "3-D SEGMENTATION OF MEDICAL STRUCTURES BY INTEGRATION OF RAYCASTING WITH ANATOMIC KNOWLEDGE," COMPUTERS & GRAPHICS, vol. 19, pp. 441-449, 1995.
Abstract:
We present a graphically interactive procedure which is used to
register a digital anatomic brain atlas with the tomographic patient
volume. Patient structures to be segmented are outlined by local
elastic deformation of corresponding objects from the anatomy model.
This is performed in voxel space using a cost minimization procedure.
The anatomic knowledge acquired in this manner is stored in a patient
specific volume dataset and guides a raycaster with respect to the
localization of object surfaces in order to control the result of the
deformation process. Thus objects, which so far could not have been
segmented appropriately or only after tedious manual editing efforts,
become accessible by physicians. We present several results
demonstrating the high quality and practicality of the method.
|
46. | KISWORO, M, VENKATESH, S, and WEST, GAW, "DETECTION OF CURVED EDGES AT SUBPIXEL ACCURACY USING DEFORMABLE MODELS," IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, vol. 142, pp. 304-312, 1995.
Abstract:
One approach to the detection of curves at subpixel accuracy involves
the reconstruction of such features from subpixel edge data points. A
new technique is presented for reconstructing and segmenting curves
with subpixel accuracy using deformable models. A curve is represented
as a set of interconnected Hermite splines forming a snake generated
from the subpixel edge information that minimises the global energy
functional integral over the set. While previous work on the
minimisation was mostly based on the Euler-Lagrange transformation, the
authors use the finite element method to solve the energy minimisation
equation. The advantages of this approach over the Euler-Lagrange
transformation approach are that the method is straightforward, leads
to positive m-diagonal symmetric matrices, and has the ability to cope
with irregular geometries such as junctions and corners. The energy
functional integral solved using this method can also be used to
segment the features by searching for the location of the maxima of the
first derivative of the energy over the elementary curve set.
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47. | Kuszyk, BS, Ney, DR, and Fishman, EK, "The current state of the art in three dimensional oncologic imaging: An overview," INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, vol. 33, pp. 1029-1039, 1995.
Abstract:
To provide an overview of the methods and clinical applications of
three dimensional (3D) medical imaging in the oncologic patient.
Methods and Materials: We briefly outline the techniques currently used
to create 3D medical images with an emphasis on their strengths and
shortcomings as they relate to oncologic imaging and radiation therapy
planning, We then discuss some of the most important and promising
oncologic applications of 3D imaging and suggest likely future
directions in this rapidly developing field.
Results: Since the first application of 3D techniques to medical data
over a decade ago, 3D medical images have evolved from relatively crude
representations of musculoskeletal abnormalities to detailed and
accurate representations of a variety of soft tissue, vascular, and
oncologic pathology. The rapid development of both computer hardware
and software coupled with the application of 3D techniques to a variety
of imaging modalities have expanded the clinical applications of this
technology dramatically.
Conclusions: 3D medical images are clinically practical tools for
oncologic evaluation and effective radiation therapy planning.
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48. | Broggi, A, and Berte, S, "Vision-based road detection in automotive systems: A real-time expectation-driven approach," JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, vol. 3, pp. 325-348, 1995.
Abstract:
The main aim of this work is the development of a vision-based road
detection system fast enough to cope with the difficult real-time
constraints imposed by moving vehicle applications. The hardware
platform, a special-purpose massively parallel system, has been chosen
to minimize system production and operational costs.
This paper presents a novel approach to expectation-driven low-level
image segmentation, which can be mapped naturally onto mesh-connected
massively parallel SIMD architectures capable of handling hierarchical
data structures. The input image is assumed to contain a distorted
version of a given template; a multiresolution stretching process is
used to reshape the original template in accordance with the acquired
image content, minimizing a potential function. The distorted template
is the process output.
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49. | KRAITCHMAN, DL, YOUNG, AA, CHANG, CN, and AXEL, L, "SEMIAUTOMATIC TRACKING OF MYOCARDIAL MOTION IN MR TAGGED IMAGES," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 14, pp. 422-433, 1995.
Abstract:
Tissue tagging using magnetic resonance (MR) imaging has enabled
quantitative noninvasive analysis of motion and deformation in vivo.
One method for MR tissue tagging is Spatial Modulation of Magnetization
(SPAMM), Manual detection and tracking of tissue tags by visual
inspection remains a time-consuming and tedious process. We have
developed an interactively guided semi-automated method of detecting
and tracking tag intersections in cardiac MR images, A template
matching approach combined with a novel adaptation of active contour
modeling permits rapid analysis of MR images. We have validated our
technique using MR SPAMM images of a silicone gel phantom with
controlled deformations. Average discrepancy between theoretically
predicted and semi-automatically selected tag intersections was 0.30 mm
+/- 0.17 [mean +/- SD, NS (P < 0.05)]. Cardiac SPAMM images of normal
volunteers and diseased patients also have been evaluated using our
technique.
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50. | MARCHANT, JA, and ONYANGO, CM, "FITTING GREY LEVEL POINT DISTRIBUTION MODELS TO ANIMALS IN SCENES," IMAGE AND VISION COMPUTING, vol. 13, pp. 3-12, 1995.
Abstract:
Point distribution models allow a compact description of an object's
shape to be found from a set of example images. In previous work by
the first author, a method of incorporating grey level information into
a PDM was developed. This paper investigates fitting such a composite
model to image data consisting of a set of images of a pig viewed from
above. Model fitting is achieved by optimizing an objective function
consisting of two components, one that measures the degree of grey
level correspondence between the model and the data, and the other that
measures how well the boundary of the model fits the data. The shape
of the objective function as the model parameters are varied is
investigated, and an optimization strategy developed. The strategy is
used to find a pig in a number of images with backgrounds of increasing
complexity. The strategy performs well with both an uncluttered and a
realistic background. The performance with a simulated noisy
background is not so good when the boundary component is included in
the objective function. This is a result of the boundary component
being more sensitive to noise in the image. In this case, it is better
to optimize with the grey level component alone. A problem is
identified when the grey level distribution changes significantly as
the pig moves under the light source. It is suggested that this could
be overcome by including variations in grey level distribution as modes
in the model.
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51. | DELANGES, P, BENOIS, J, and BARBA, D, "ACTIVE CONTOURS APPROACH TO OBJECT TRACKING IN IMAGE SEQUENCES WITH COMPLEX BACKGROUND," PATTERN RECOGNITION LETTERS, vol. 16, pp. 171-178, 1995.
Abstract:
Active contour models (''snakes'') are a powerful tool for deformable
object tracking in moving images. But the existing snake models are
not well-adapted for tracking corners and objects on a complex
background. In this paper, we present a novel active contour model,
the ''Adjustable Polygons'', which is a set of active segments that can
fit any object shape (including corners). A new energy based on
textural characteristics of objects is also proposed, in order to
resolve conflict situations while tracking objects on multiple contour
background.
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52. | DAVATZIKOS, CA, and PRINCE, JL, "AN ACTIVE CONTOUR MODEL FOR MAPPING THE CORTEX," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 14, pp. 65-80, 1995.
Abstract:
A new active contour model for finding and mapping the outer cortex in
brain images is developed, A cross-section of the brain cortex is
modeled as a ribbon, and a constant speed mapping of its spine is
sought. A variational formulation, an associated force balance
condition, and a numerical approach are proposed to achieve this goal,
The primary difference between this formulation and that of snakes is
in the specification of the external force acting on the active
contour. A study of the uniqueness and fidelity of solutions is made
through convexity and frequency domain analyses, and a criterion for
selection of the regularization coefficient is developed. Examples
demonstrating the performance of this method on simulated and real data
are provided.
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53. | ASHTON, EA, BERG, MJ, PARKER, KJ, WEISBERG, J, CHEN, CW, and KETONEN, L, "SEGMENTATION AND FEATURE-EXTRACTION TECHNIQUES, WITH APPLICATIONS TO MRI HEAD STUDIES," MAGNETIC RESONANCE IN MEDICINE, vol. 33, pp. 670-677, 1995.
Abstract:
To obtain a three-dimensional reconstruction of the hippocampus from a
volumetric MRI head study, it is necessary to separate that structure
not only from the surrounding white matter, but also from contiguous
areas of gray matter-the amygdala and cerebral cortex. At present it is
necessary for a physician to manually segment the hippocampus on each
slice of the volume to obtain such a reconstruction. This process is
time consuming, and is subject to inter- and intra-operator variation
as well as large discontinuities between slices. We propose a novel
technique, making use of a combination of gray scale and edge-detection
algorithms and some a priori knowledge, by which a computer may make an
unsupervised identification of a given structure through a series of
contiguous images. This technique is applicable even if the structure
includes so-called false contours or missing contours. Applications
include three-dimensional reconstruction of difficult-to-segment
regions of the brain, and volumetric measurements of structures from
series of two-dimensional images.
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54. | WOLBERG, WH, STREET, WN, and MANGASARIAN, OL, "IMAGE-ANALYSIS AND MACHINE LEARNING APPLIED TO BREAST-CANCER DIAGNOSIS AND PROGNOSIS," ANALYTICAL AND QUANTITATIVE CYTOLOGY AND HISTOLOGY, vol. 17, pp. 77-87, 1995.
Abstract:
Fine needle aspiration (FNA) accuracy is limited by, among other
factors, the subjective interpretation of the aspirate. We have
increased breast FNA accuracy by coupling digital image analysis
methods with machine learning techniques. Additionally, our
mathematical approach captures nuclear features (''grade'') that are
prognostically more accurate than are estimates based on tumor size and
lymph node status. An interactive computer system evaluates, diagnoses
and determines prognosis based on nuclear features derived directly
from a digital scan of FNA slides. A consecutive series of 569 patients
provided the data for the diagnostic study. A 166-patient subset
provided the data for the prognostic study. An additional 75
consecutive, new patients provided samples to test the diagnostic
system. The projected prospective accuracy of the diagnostic system was
estimated to be 97% by 10-fold cross-validation, and the actual
accuracy on 75 new samples runs 100%. The projected prospective
accuracy of the prognostic system was estimated to be 86% by
leave-one-out testing.
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55. | NOBLE, JA, "FROM INSPECTION TO PROCESS UNDERSTANDING AND MONITORING - A VIEW ON COMPUTER VISION IN MANUFACTURING," IMAGE AND VISION COMPUTING, vol. 13, pp. 197-214, 1995.
Abstract:
We describe some of the current challenges in developing and validating
computer vision algorithms for manufacturing applications. We focus on
the general theme of template-based processing, where geometric
templates provide a basis for local feature analysis, registration and
recognition (via constraint-based modelling) and model adaptation using
statistical methods. We describe recent successful applications of
template-based techniques in the areas of manufacturing part inspection
and process understanding and monitoring. We also examine the question
'Why are there so few computer vision applications in manufacturing?'
We suggest that two of the major bottlenecks remain speed of algorithm
development and how to validate algorithm performance with a limited
data set. Finally, we identify some of what we see as emerging and
future potential application areas of computer vision methods in
manufacturing, where the current trend is to provide tools for
continuous product improvement rather than (final) product inspection,
and 3D measurement capabilities.
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56. | Bothe, HH, and vonBotticher, N, "Key-picture selection for the analysis of visual speech with fuzzy methods," ADVANCES IN INTELLIGENT COMPUTING - IPMU '94, LECTURE NOTES IN COMPUTER SCIENCE, vol. 945, pp. 577-583, 1995.
Abstract:
The goal of the described work is to model visual articulation
movements of prototypic speakers with respect to custom-made text A
language-wide extension of the motion model leads to a visible speech
synthesis and further more to an artificial computer trainer for
speechreading. The developed model is based on a set of specific video
key-pictures and the interpolation of interim pictures. The key-picture
selection is realized by a fuzzy-c-means classification algorithm.
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57. | AYACHE, N, "MEDICAL COMPUTER VISION, VIRTUAL-REALITY AND ROBOTICS," IMAGE AND VISION COMPUTING, vol. 13, pp. 295-313, 1995.
Abstract:
The automated analysis of 3D medical images can improve both diagnosis
and therapy significantly. This automation raises a number of new
fascinating research problems in the fields of computer vision,
graphics and robotics. In this paper, I propose a list of such problems
after a review of the current major 3D imaging modalities, and a
description of the related medical needs. I then present some of the
past and current work done in our research group EPIDAURE* at INRIA, on
the following topics: segmentation of 3D images; 3D shape modelling; 3D
rigid and nonrigid registration; 3D motion analysis; and 3D simulation
of therapy. Most topics are discussed in a synthetic manner, and
illustrated by results. Rigid matching is treated more thoroughly as an
illustration of a transfer from computer vision towards 3D image
processing. The later topics are illustrated by preliminary results,
and a number of promising research tracks are suggested.
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58. | SCHWARZINGER, M, NOLL, D, and VONSEELEN, W, "OBJECT RECOGNITION WITH CONSTRAINED ELASTIC MODELS," MATHEMATICAL AND COMPUTER MODELLING, vol. 22, pp. 163-184, 1995.
Abstract:
We present a model-based method for object identification in images of
natural scenes. It has successfully been implemented for the
classification of cars based on their rear view. In a first step,
characteristic features such as lines and corners are detected within
the image. Generic models of object-classes, described by the same set
of features, are stored in a database. Each model represents a whole
class of objects (e.g., passenger cars, vans, big trucks). In a
preprocessing stage, the most probable object is selected by means of a
corner-feature based Hough transform. This transformation also suggests
the position and scale of the object in the image. Guided by similarity
measures, the model is then aligned with image features using a
matching algorithm based on the elastic net technique [1]. During this
iterative process, the model is allowed to undergo changes in scale,
position and certain deformations. Deformations are kept within limits
such that one model can fit to all objects belonging to the same class,
but not to objects of other classes. In each iteration step, quantities
to assess the matching process are obtained.
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59. | GOSHTASBY, A, and TURNER, DA, "SEGMENTATION OF CARDIAC CINE MR-IMAGES FOR EXTRACTION OF RIGHT AND LEFT-VENTRICULAR CHAMBERS," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 14, pp. 56-64, 1995.
Abstract:
A two-stage algorithm for extraction of the ventricular chambers
(endocardial surfaces) in flow-enhanced magnetic resonance images is
described, In the first stage, the approximate locations and sizes of
the endocardial surfaces are determined by intensity thresholding. In
the second stage, points on each approximated surface are repositioned
to nearest locally maximum gradient magnitude points and a generalized
cylinder is fitted to them, Examples of ventricular chambers in cine MR
images determined by this algorithm are presented.
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60. | HOWARTH, R, "INTERPRETING A DYNAMIC AND UNCERTAIN WORLD - HIGH-LEVEL VISION," ARTIFICIAL INTELLIGENCE REVIEW, vol. 9, pp. 37-63, 1995.
Abstract:
When interpreting a dynamic and uncertain world it is important to have
a high-level vision component that can guide the reasoning of the whole
vision system. This guidance is provided by an attentional mechanism
that exploits knowledge of the specific problem being solved. Here we
survey work relevant to the development of such an attentional
mechanism, using surveillance as an application domain to tie together
issues of spatial representation, events, behaviour, control and
planning. The paper culminates in a brief description of HIVIS-WATCHER
a program that makes use of all these areas.
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61. | SCLAROFF, S, and PENTLAND, AP, "MODAL MATCHING FOR CORRESPONDENCE AND RECOGNITION," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 17, pp. 545-561, 1995.
Abstract:
Modal matching is a new method for establishing correspondences and
computing canonical descriptions, The method is based on the idea of
describing objects in terms of generalized symmetries, as defined by
each object's eigenmodes. The resulting modal description is used for
object recognition and categorization, where shape similarities are
expressed as the amounts of modal deformation energy needed to align
the two objects, In general, modes provide a global-to-local ordering
of shape deformation and thus allow for selecting which types of
deformations are used in object alignment and comparison, In contrast
to previous techniques, which required correspondence to be computed
with an initial or prototype shape, modal matching utilizes a new type
of finite element formulation that allows for an object's eigenmodes to
be computed directly from available image information, This improved
formulation provides greater generality and accuracy, and is applicable
to data of any dimensionality, Correspondence results with 2D contour
and point feature data are shown, and recognition experiments with 2D
images of hand tools and airplanes are described.
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62. | GOSHTASBY, A, and SHYU, HL, "EDGE-DETECTION BY CURVE-FITTING," IMAGE AND VISION COMPUTING, vol. 13, pp. 169-177, 1995.
Abstract:
Edge detection is formulated as a curve fitting problem. First,
high-gradient pixels are grouped into elongated regions and then a
curve is fitted to each. The curve fitting method used in this work
does not require solving a system of equations, and therefore is fast.
Examples of edge detection by curve fitting on synthetic and real
images are presented, and results obtained are compared with those
determined by the Laplacian of Gaussian operator.
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63. | WOLBERG, WH, STREET, WN, HEISEY, DM, and MANGASARIAN, OL, "COMPUTERIZED BREAST-CANCER DIAGNOSIS AND PROGNOSIS FROM FINE-NEEDLE ASPIRATES," ARCHIVES OF SURGERY, vol. 130, pp. 511-516, 1995.
Abstract:
Objective: To use digital image analysis and machine learning to (1)
improve breast mass diagnosis based on fine-needle aspirates and (2)
improve breast cancer prognostic estimations.
Design: An interactive computer system evaluates, diagnoses, and
determines prognosis based on cytologic features derived from a digital
scan of fine-needle aspirate slides.
Setting: The University of Wisconsin (Madison) Departments of Computer
Science and Surgery and the University of Wisconsin Hospital and
Clinics.
Patients: Five hundred sixty-nine consecutive patients (212 with cancer
and 357 with benign masses) provided the data for the diagnostic
algorithm, and an additional 118 (31 with malignant masses and 87 with
benign masses) consecutive, new patients tested the algorithm. One
hundred ninety of these patients with invasive cancer and without
distant metastases were used for prognosis.
Interventions: Surgical biopsy specimens were taken from all cancers
and some benign masses. The remaining cytologically benign masses were
followed up for a year and surgical biopsy specimens were taken if they
changed in size or character. Patients with cancer received standard
treatment.
Outcome Measures: Cross validation was used to project the accuracy of
the diagnostic algorithm and to determine the importance of prognostic
features. In addition, the mean errors were calculated between the
actual times of distant disease occurrence and the times predicted
using various prognostic features. Statistical analyses were also done.
Results The predicted diagnostic accuracy was 97% and the actual
diagnostic accuracy on 118 new samples was 100%. Tumor size and lymph
node status were weak prognosticators compared with nuclear features,
in particular those measuring nuclear size. Compared with the actual
time for recurrence, the mean error of predicted times for recurrence
with the nuclear features was 17.9 months and was 20.1 months with
tumor size and lymph node status (P=.11).
Conclusion: Computer technology will improve breast fine-needle
aspirate accuracy and prognostic estimations.
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64. | LUNDERVOLD, A, and STORVIK, G, "SEGMENTATION OF BRAIN PARENCHYMA AND CEREBROSPINAL-FLUID IN MULTISPECTRAL MAGNETIC-RESONANCE IMAGES," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 14, pp. 339-349, 1995.
Abstract:
This paper presents a new method to segment brain parenchyma and
cerebrospinal fluid spaces automatically in routine axial spin echo
multispectral MR images. The algorithm simultaneously incorporates
information about anatomical boundaries (shape) and tissue signature
(grey scale) using a priori knowledge. The head and brain are divided
into four regions and seven different tissue types. Each tissue type c
is modeled by a multivariate Gaussian distribution N(mu(c), Sigma(c)).
Each region is associated with a finite mixture density corresponding
to its constituent tissue types, Initial estimates of tissue parameters
{mu(c), Sigma(c)}(c=1,...,7) are obtained from L-means clustering of a
single slice used for training. The first algorithmic step uses the
EM-algorithm for adjusting the initial tissue parameter estimates to
the MR data of new patients, The second step uses a recently developed
model of dynamic contours to detect three simply closed nonintersecting
curves in the plane, constituting the arachnoid/dura mater boundary of
the brain, the border between the subarachnoid space and brain
parenchyma, and the inner border of the parenchyma toward the lateral
ventricles, The model, which is formulated by energy functions in a
Bayesian framework, incorporates a priori knowledge, smoothness
constraints, and updated tissue type parameters, Satisfactory maximum a
posteriori probability estimates of the closed contour curves defined
by the model were found using simulated annealing.
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65. | ONYANGO, CM, MARCHANT, JA, and RUFF, BP, "MODEL-BASED LOCATION OF PIGS IN SCENES," COMPUTERS AND ELECTRONICS IN AGRICULTURE, vol. 12, pp. 261-273, 1995.
Abstract:
Point distribution models (PDMs) allow a compact description of an
object's shape to be found from a set of example images. In previous
work by the second author a method of incorporating grey level
information into a PDM was developed. Further work investigated fitting
such a composite model to image data consisting of a set of images of a
pig viewed from above. This paper describes work on images containing
more than one pig.
A technique for initialising the model is used which searches the image
for ridges in the grey level landscape. These generally lie along the
backbone of the animal and provide a good starting point for automatic
fitting. By minimising an objective function which measures the
difference in grey level and the error in boundary correspondence, an
accurate fit of model to data is obtained.
Ridge detection initialises the model to within +/-12 pixels of the
object. Strict limits on the boundaries of the search space constrain
the minimisation process allowing convergence to the true minimum. The
resulting fit is good even for objects which are partially obscured.
Poor final values of the objective function allow the detection of
erroneous results.
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66. | HERAULT, L, and HORAUD, R, "SMOOTH CURVE EXTRACTION BY MEAN-FIELD ANNEALING," ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE, vol. 13, pp. 281-300, 1995.
Abstract:
In this paper, we attack the figure-ground discrimination problem from
a combinatorial optimization perspective. In general, the solutions
proposed in the past solved this problem only partially: either the
mathematical model encoding the figure-ground problem was too simple or
the optimization methods that were used were not efficient enough or
they could not guarantee to find the global minimum of the cost
function describing the figure-ground model. The method that we devised
and which is described in this paper is tailored around the following
contributions. First, we suggest a mathematical model encoding the
figure-ground discrimination problem that makes explicit a definition
of shape (or figure) based on cocircularity, smoothness, proximity, and
contrast. This model consists of building a cost function on the basis
of image element interactions. Moreover, this cost function fits the
constraints of an interacting spin system, which in turn is a well
suited physical model to solve hard combinatorial optimization
problems. Second, we suggest a combinatorial optimization method for
solving the figure-ground problem, namely mean field annealing which
combines the mean field approximation and annealing. Mean field
annealing may well be viewed as a deterministic approximation of
stochastic methods such as simulated annealing. We describe in detail
the theoretical bases of this method, derive a computational model, and
provide a practical algorithm. Finally, some experimental results are
shown for both synthetic and real images.
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67. | YAMAMOTO, K, "OPTIMIZATION APPROACHES TO CONSTRAINT SATISFACTION PROBLEMS IN COMPUTER VISION," IMAGE AND VISION COMPUTING, vol. 13, pp. 335-340, 1995.
Abstract:
This paper describes several new image understanding methods based on
parallel operation. There are several constraint satisfaction
approaches using an energy minimization. We show how we reconstruct
three-dimensional surfaces from contours without elevation data and
sparse points of known elevation data using this approach. We also
introduce Active Net using this approach, and apply this model to
segmentation and binocular stereo matching. We experimented with these
energy minimization approaches to solve the problems of early and
intermediate levels of computer vision, and show some of the results of
our recent research.
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68. | VIEREN, C, CABESTAING, F, and POSTAIRE, JG, "CATCHING MOVING-OBJECTS WITH SNAKES FOR MOTION TRACKING," PATTERN RECOGNITION LETTERS, vol. 16, pp. 679-685, 1995.
Abstract:
We propose an efficient method for tracking several objects moving
through a sequence of monocular images against a non-uniform
background. Each object entering the scene is intercepted by an active
contour model which locks on it as long as it moves in the scene. The
procedure does not necessitate an interactive initialization. Some
results are presented in case of real traffic scenes.
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69. | PARVIN, BA, PENG, C, JOHNSTON, W, and MAESTRE, FM, "TRACKING OF TUBULAR MOLECULES FOR SCIENTIFIC APPLICATIONS," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 17, pp. 800-805, 1995.
Abstract:
In this paper, we present a system for detection and tracking of
tubular molecules in images. The automatic detection and
characterization of the shape, location, and motion of these molecules
can enable new laboratory protocols in several scientific disciplines.
The uniqueness of the proposed system is twofold: At the macro level,
the novelty of the system lies in the integration of object
localization and tracking using geometric properties; at the micro
level, in the use of high and low level constraints to model the
detection and tracking subsystem. The underlying philosophy for object
detection is to extract perceptually significant features from the
pixel level image, and then use these high level cues to refine the
precise boundaries. In the case of tubular molecules, the perceptually
significant features are antiparallel line segments or, equivalently,
their axis of symmetries. The axis of symmetry infers a coarse
description of the object in terms of a bounding polygon. The polygon
then provides the necessary boundary condition for the refine ment
process, which is based on dynamic programming. For tracking the object
in a time sequence of images, the refined contour is then projected
onto each consecutive frame.
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70. | WESSELINK, W, and VELTKAMP, RC, "INTERACTIVE DESIGN OF CONSTRAINED VARIATIONAL CURVES," COMPUTER AIDED GEOMETRIC DESIGN, vol. 12, pp. 533-546, 1995.
Abstract:
A constrained variational curve is a curve that minimizes some energy
functional under certain interpolation constraints. Modeling curves
using constrained variational principles is attractive, because the
designer is not bothered with the precise representation of the curve
(e.g. control points). Until now, the modeling of variational curves is
mainly done by means of constraints. If such a curve of least energy is
deformed locally (e.g, by moving its control points) the concept of
energy minimization is lost. In this paper we introduce deform
operators with built-in energy terms. We have tested our ideas in a
prototype system for modeling uniform B-spline curves. Through the use
of widgets, the user can interactively modify the range of influence
and other properties of the operators. Experiments show that these
operators offer a very intuitive way of modeling.
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71. | PEARSON, DE, "DEVELOPMENTS IN MODEL-BASED VIDEO CODING," PROCEEDINGS OF THE IEEE, vol. 83, pp. 892-906, 1995.
Abstract:
This paper reports on current developments in the area of model-based
video coding, a technique which shows promise of achieving very, large
bit-rate reductions for moving images. After an introduction and
historical review, advances are summarized in several areas, among them
improved 3D tracking of the human head and of facial expressions, the
use of muscle-driven model animation with skin synthesis, techniques
for luminance compensation, and switched coders. Bit rates ranging from
64 kb/s down to about 1 kb/s have been obtained using head-and-shoulder
video sequences. Problems with model-based methods are identified and
future developments in both CBR and VER transmission discussed.
|
72. | SNELL, JW, MERICKEL, MB, ORTEGA, JM, GOBLE, JC, BROOKEMAN, JR, and KASSELL, NF, "MODEL-BASED BOUNDARY ESTIMATION OF COMPLEX OBJECTS USING HIERARCHICAL ACTIVE SURFACE TEMPLATES," PATTERN RECOGNITION, vol. 28, pp. 1599-1609, 1995.
Abstract:
A method for the segmentation of complex, three-dimensional objects
using hierarchical active surface templates is presented. The templates
consist of one or more active surface models which are specified
according to a priori knowledge about the expected shape and location
of the desired object. This allows complex objects to be naturally
modeled as collections of simple subparts which are geometrically
constrained. The template is adaptively deformed by the
three-dimensional image data in which it is initialized such that the
template boundaries are brought into correspondence with the assumed
image object. An external energy field is developed based on a vector
distance transform such that the surfaces are deformed according to
object shape. The method is demonstrated by the segmentation of the
human brain from three-dimensional magnetic resonance images of the
head given an a priori model of a normal brain.
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73. | Wong, WH, and Ip, HHS, "Force-driven optimization for correspondence establishment," IMAGE ANALYSIS APPLICATIONS AND COMPUTER GRAPHICS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1024, pp. 43-50, 1995.
Abstract:
Correspondence establishment has been a difficult problem in machine
vision. In this paper, we present an optimization technique for the
task. The geometric constraints to the solution are formulated as
forces, which are combined to provide clue for mapping between two sets
of points such that the geometric constraints are best satisfied. The
strong point of this method is that it is easy to integrate several
sources of information to obtain a solution while keeping the decision
simple, and does not suffer from the uncontrollable flexibility as in
active contour models. We illustrate the method with the problem of
establishing correspondence between parallel curves.
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74. | KIMIA, BB, TANNENBAUM, AR, and ZUCKER, SW, "SHAPES, SHOCKS, AND DEFORMATIONS .1. THE COMPONENTS OF 2-DIMENSIONAL SHAPE AND THE REACTION-DIFFUSION SPACE," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 15, pp. 189-224, 1995.
Abstract:
We undertake to develop a general theory of two-dimensional shape by
elucidating several principles which any such theory should meet. The
principles are organized around two basic intuitions: first, if a
boundary were changed only slightly, then, in general, its shape would
change only slightly. This leads us to propose an operational theory of
shape based on incremental contour deformations. The second intuition
is that not all contours are shapes, but rather only those that can
enclose ''physical'' material. A theory of contour deformation is
derived from these principles, based on abstract conservation
principles and Hamilton-Jacobi theory. These principles are based on
the work of Sethian (1985a, c), the Osher-Sethian (1988), level set
formulation the classical shock theory of Lax (1971; 1973), as well as
curve evolution theory for a curve evolving as a function of the
curvature and the relation to geometric smoothing of
Gage-Hamilton-Grayson (1986; 1989). The result is a characterization of
the computational elements of shape: deformations, parts, bends, and
seeds, which show where to place the components of a shape. The theory
unifies many of the diverse aspects of shapes, and leads to a space of
shapes (the reaction/diffusion space), which places shapes within a
neighborhood of ''similar'' ones. Such similarity relationships
underlie descriptions suitable for recognition.
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75. | WOLBERG, WH, STREET, WN, HEISEY, DM, and MANGASARIAN, OL, "COMPUTER-DERIVED NUCLEAR GRADE AND BREAST-CANCER PROGNOSIS," ANALYTICAL AND QUANTITATIVE CYTOLOGY AND HISTOLOGY, vol. 17, pp. 257-264, 1995.
Abstract:
Visual assessments of nuclear grade are subjective yet still
prognostically important. Now, computer-based analytical techniques can
objectively and accurately measure size, shape and texture features,
which constitute nuclear grade. The cell samples used in this study
were obtained by fine needle aspiration (FNA) during the diagnosis of
187 consecutive patients with invasive breast cancer. Regions of FNA
preparations to be analyzed were digitized and displayed on a computer
monitor. Nuclei to be analyzed were roughly outlined by an operator
using a mouse. Next, the computer generated a ''snake'' that precisely
enclosed each designated nucleus. Ten nuclear features were then
calculated for each nucleus based on these snakes. These results were
analyzed statistically and by an inductive machine learning technique
that we developed and call ''recurrence surface approximation'' (RSA).
Both the statistical and RSA machine learning analyses demonstrated
that computer-derived nuclear features are prognostically move
important than are the classic prognostic features, tumor size and
lymph node status.
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76. | PANKANTI, S, and JAIN, AK, "INTEGRATING VISION MODULES - STEREO, SHADING, GROUPING, AND LINE LABELING," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 17, pp. 831-842, 1995.
Abstract:
It is generally agreed that individual visual cues are fallible and
often ambiguous. This has generated a lot of interest in design of
integrated vision systems which are expected to give a reliable
performance in practical situations. The design of such systems is
challenging since each vision module works under a different and
possibly conflicting set of assumptions. We have proposed and
implemented a multiresolution system which integrates perceptual
organization (grouping), segmentation, stereo, shape from shading, and
line labeling modules. We demonstrate the efficacy of our approach
using images of several different realistic scenes. The output of the
integrated system is shown to be insensitive to the constraints imposed
by the individual modules. The numerical accuracy of the recovered
depth is assessed in case of synthetically generated data. Finally, we
have qualitatively evaluated our approach by reconstructing geons from
the depth data obtained from the integrated system. These results
indicate that integrated vision systems are likely to produce better
reconstruction of the input scene than the individual modules.
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77. | YOUNG, AA, KRAITCHMAN, DL, DOUGHERTY, L, and AXEL, L, "TRACKING AND FINITE-ELEMENT ANALYSIS OF STRIPE DEFORMATION IN MAGNETIC-RESONANCE TAGGING," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 14, pp. 413-421, 1995.
Abstract:
Magnetic resonance tissue tagging allows noninvasive in vivo
measurement of soft tissue deformation, Planes of magnetic saturation
are created, orthogonal to the imaging plane, which form dark lines
(stripes) in the image, We describe a method for tracking stripe motion
in the image plane, and show how this information can be incorporated
into a finite element model of the underlying deformation, Human heart
data were acquired from several imaging planes in different
orientations and were combined using a deformable model of the left
ventricle wall, Each tracked stripe point provided information on
displacement orthogonal to the original tagging plane, i.e., a
one-dimensional (1-D) constraint on the motion, Three-dimensional (3-D)
motion and deformation was then reconstructed by fitting the model to
the data constraints by linear least squares, The average root mean
squared (rms) error between tracked stripe points and predicted model
locations was 0.47 mm (n = 3100 points). In order to validate this
method and quantify the errors involved, we applied it to images of a
silicone gel phantom subjected to a known, well-controlled, 3-D
deformation. The finite element strains obtained were compared to an
analytic model of the deformation known to be accurate in the central
axial plane of the phantom, The average rms errors were 6% in both the
reconstructed shear strains and 16% in the reconstructed radial normal
strain.
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1996 |
78. | Nakajima, C, and Yazawa, T, "A recognition method of facility drawings and street maps utilizing the facility management database," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E79D, pp. 555-560, 1996.
Abstract:
This paper proposes a new approach for inputting handwritten
Distribution Facility Drawings (DFD) and their maps into a computer
automatically by using the Facility Management Database (FMD). Our
recognition method makes use of external information for drawing/map
recognition. It identifies each electric-pole symbol and support cable
symbol on drawings simply by consulting the FMD. Other symbols such as
transformers and electric wires can be placed on drawings
automatically. In this positioning of graphic symbols, we present an
automatic adjustment method of a symbol's position on the latest
digital maps. When a contradiction is unsolved due to an inconsistency
between the content of the DFD and the FMD, the system requests a
manual feedback from the operator. Furthermore, it uses the
distribution network of the DFD to recognize the street lines on the
maps which aren't computerized. This can drastically reduce the cost
for computerizing drawings and maps.
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79. | Cohen, I, and Cohen, LD, "A hybrid hyperquadric model for 2-D and 3-D data fitting," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 63, pp. 527-541, 1996.
Abstract:
We present in this paper a new curve and surface implicit model. This
implicit model is based on hyperquadrics and allows a local and global
control of the shape and a wide variety of allowable shapes. We define
a hybrid hyperquadric model by introducing implicitly some local
properties on a global shape model. The advantage of our model is that
it describes global and local properties through a unique implicit
equation, yielding a representation of the shape by means of its
parameters, independently of the chosen numerical resolution. The data
fitting is obtained through the minimization of energy, modeling the
attraction to data independently of the implicit description of the
shape, After studying the geometry of hyperquadrics and how the shape
deforms when we modify slightly its implicit equation, we are able to
define an algorithm for automatic refining of the fit by adding an
adequate term to the implicit representation, This geometric approach
malt:es possible an efficient description of the data points and an
automatic tuning of the fit according to the desired accuracy. (C) 1996
Academic Press, Inc.
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80. | Qian, RJ, and Huang, TS, "Optimal edge detection in two-dimensional images," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 5, pp. 1215-1220, 1996.
Abstract:
This paper presents a new edge detection scheme that detects
two-dimensional (2-D) edges by a curve-segment-based detection
functional guided by the zero-crossing contours of the
Laplacian-of-Gaussian (LOG) to approach the true edge locations. The
detection functional is shown to be optimal in terms of signal-to-noise
ratio (SNR) and edge localization accuracy; it also preserves the nice
scaling property held uniquely by the LOG in scale space.
|
81. | Fua, P, and Leclerc, YG, "Taking advantage of image-based and geometry-based constraints to recover 3-D surfaces," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 64, pp. 111-127, 1996.
Abstract:
A unified framework for 3-D shape reconstruction allows us to combine
image-based and geometry-based information sources. The image
information is akin to stereo and shape-from-shading, while the
geometric information may be provided in the form of 3-D points, 3-D
features, or 2-D silhouettes. A formal integration framework is
critical in recovering complicated surfaces because the information
from a single source is often insufficient to provide a unique answer.
Our approach to shape recovery is to deform a generic object-centered
3-D representation of the surface so as to minimize an objective
function, This objective function is a weighted sum of the
contributions of the various information sources. We describe these
various terms individually, our weighting scheme, and our optimization
method, Finally, we present results on a number of difficult images of
real scenes for which a single source of information would have proved
insufficient. (C) 1996 Academic Press, Inc.
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82. | Mitiche, A, and Bouthemy, P, "Computation and analysis of image motion: A synopsis of current problems and methods," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 19, pp. 29-55, 1996.
Abstract:
The goal of this paper is to offer a structured synopsis of the
problems in image motion computation and analysis, and of the methods
proposed, exposing the underlying models and supporting assumptions. A
sufficient number of pointers to the literature will be given,
concentrating mostly on recent contributions. Emphasis will be on the
detection, measurement and segmentation of image motion. Tracking, and
deformable motion isssues will be also addressed. Finally, a number of
related questions which could require more investigations will be
presented.
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83. | Ge, YR, Fitzpatrick, JM, Dawant, BM, Bao, J, Kessler, RM, and Margolin, RA, "Accurate localization of cortical convolutions in MR brain images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 418-428, 1996.
Abstract:
Analysis of brain images often requires accurate localization of
cortical convolutions. Although magnetic resonance (MR) brain images
offer sufficient resolution for identifying convolutions in theory, the
nature of tomographic imaging prevents clear definition of convolutions
in individual slices, Existing methods for solving this problem rely on
heuristic adaptation of brain atlases created from a small number of
individuals, These methods do not usually provide high accuracy because
of large biological variations among individuals. We propose to
localize convolutions by linking realistic visualizations of the
cortical surface with the original image volume. We have developed a
system so that a user can quickly localize key convolutions in several
visualizations of an entire brain surface, Because of the links between
the visualizations and the original volume, these convolutions are
simultaneously localized in the original image slices, In the process
of our development, we have implemented a fast and easy method for
visualizing cortical surfaces in MR images, thereby making our scheme
usable in practical applications.
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84. | Thompson, P, and Toga, AW, "A surface-based technique for warping three-dimensional images of the brain," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 402-417, 1996.
Abstract:
We have devised, implemented, and tested a fast, spatially accurate
technique for calculating the high-dimensional deformation held
relating the brain anatomies of an arbitrary pair of subjects, The
resulting three-dimensional (3-D) deformation map can be used to
quantify anatomic differences between subjects or within the same
subject over time and to transfer functional information between
subjects or integrate that information on a single anatomic template.
The new procedure is based on developmental processes responsible for
variations in normal human anatomy and is applicable to 3-D brain
images in general, regardless of modality, Hybrid surface models known
as Chen surfaces (based on superquadrics and spherical harmonics) are
used to efficiently initialize 3-D active surfaces, and these then
extract from both scans the developmentally fundamental surfaces of the
ventricles and cortex. The construction of extremely complex surface
deformation maps on the internal cortex is made easier by budding a
generic surface structure to model it, Connected systems of parametric
meshes model several deep sulci whose trajectories represent critical
functional boundaries, These sulci are sufficiently extended inside the
brain to reflect subtle and distributed variations in neuroanatomy
between subjects. The algorithm then calculates the high-dimensional
volumetric warp (typically with 384(2) x 256 x 3 approximate to 0.1
billion degrees of freedom) deforming one 3-D scan into structural
correspondence with the other. Integral distortion functions are used
to extend the deformation held required to elastically transform nested
surfaces to their counterparts in the target scan. The algorithm's
accuracy is tested, by warping 3-D magnetic resonance imaging (MRI)
volumes from normal subjects and Alzheimer's patients, and by warping
full-color 1024(3) digital cryosection volumes of the human head onto
MRI volumes, Applications are discussed, including the transfer of
multisubject 3-D functional, vascular, and histologic maps onto a
single anatomic template; the mapping of 3-D brain atlases onto the
scans of new subjects; and the rapid detection, quantification, and
mapping of local shape changes in 3-D medical images in disease and
during normal or abnormal growth and development.
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85. | Cohen, LD, "Auxiliary variables and two-step iterative algorithms in computer vision problems," JOURNAL OF MATHEMATICAL IMAGING AND VISION, vol. 6, pp. 59-83, 1996.
Abstract:
We present a new mathematical formulation of some curve and surface
reconstruction algorithms by the introduction of auxiliary variables.
For deformable models and templates, the extraction of a shape is
obtained through the minimization of an energy composed of an internal
regularization term (not necessary in the case of parametric models)
and an external attraction potential. Two-step iterative algorithms
have been often used where, at each iteration, the model is first
locally deformed according to the potential data attraction and then
globally smoothed (or fitted in the parametric case).
We show how these approaches can be interpreted as the introduction of
auxiliary variables and the minimization of a two-variables energy. The
first variable corresponds to the original model we are looking for,
while the second variable represents an auxiliary shape close to the
first one. This permits to transform an implicit data constraint
defined by a non convex potential into an explicit convex
reconstruction problem. This approach is much simpler since each
iteration is composed of two simple to solve steps. Our formulation
permits a more precise setting of parameters in the iterative scheme to
ensure convergence to a minimum.
We show some mathematical properties and results on this new auxiliary
problem, in particular when the potential is a function of the distance
to the closest feature point. We then illustrate our approach for some
deformable models and templates.
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86. | Malladi, R, Sethian, JA, and Vemuri, BC, "A fast level set based algorithm for topology-independent shape modeling," JOURNAL OF MATHEMATICAL IMAGING AND VISION, vol. 6, pp. 269-289, 1996.
Abstract:
Shape modeling is an important constituent of computer vision as well
as computer graphics research. Shape models aid the tasks of object
representation and recognition. This paper presents a new approach to
shape modeling which retains some of the attractive features of
existing methods, and overcomes some of their limitations. Our
technique can be applied to model arbitrarily complex shapes, which
include shapes with significant protrusions, and to situations where no
a priori assumption about the object's topology is made. A single
instance of our model, when presented with an image having more than
one object of interest, has the ability to split freely to represent
each object. This method is based on the ideas developed by Osher and
Sethian to model propagating solid/liquid interfaces with
curvature-dependent speeds. The interface (front) is a closed,
nonintersecting, hypersurface flowing along its gradient field with
constant speed or a speed that depends on the curvature. It is moved by
solving a ''Hamilton-Jacobi'' type equation written for a function in
which the interface is a particular level set. A speed term synthesized
from the image is used to stop the interface in the vicinity of object
boundaries. The resulting equation of motion is solved by employing
entropy-satisfying upwind finite difference schemes. We also introduce
a new algorithm for rapid advancement of the front using what we call a
narrow-band update scheme. The efficacy of the scheme is demonstrated
with numerical experiments on low contrast medical images.
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87. | Zhang, SQ, Douglas, MA, Yaroslavsky, L, Summers, RM, Dilsizian, V, Fananapazir, L, and Bacharach, SL, "A Fourier based algorithm for tracking SPAMM tags in gated magnetic resonance cardiac images," MEDICAL PHYSICS, vol. 23, pp. 1359-1369, 1996.
Abstract:
A method is described for automatically tracking spatial modulation of
magnetization tag lines on gated cardiac images. The method differs
from previously reported methods in that it uses Fourier based spatial
frequency and phase information to separately track horizontal and
vertical tag lines. Use of global information from the frequency
spectrum of an entire set of tag lines was hypothesized to result in a
robust algorithm with decreased sensitivity to noise. The method was
validated in several ways: first, actual tagged cardiac images at end
diastole were deformed known amounts, and the algorithm's predictions
compared to the known deformations. Second, tagged, gated images of the
thigh muscle (assumed to have similar signal to noise characteristics
as cardiac images, but to not deform with time) were created. Again the
algorithmic predictions could be compared to the known (zero magnitude)
deformations and to thigh images which had been artificially deformed.
Finally, actual cardiac tagged images were acquired, and comparisons
made between manual, visual, determinations of tag line locations, and
those predicted by the algorithm. At 0.5 T, the mean bias of the method
was <0.34 mm even at large deformations and at late (noisy) times. The
standard deviation of the method, estimated from the tagged thigh
images, was <0.7 mm even at late times. The method may be expected to
have even lower error at higher field strengths.
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88. | Eviatar, H, and Somorjai, RL, "A fast, simple active contour algorithm for biomedical images," PATTERN RECOGNITION LETTERS, vol. 17, pp. 969-974, 1996.
Abstract:
A new method for the application of active contours to biomedical
images is described. The new approach, which involves extensive
modification of the internal energy function acid a different method of
minimising the energy functional, yields rapid, excellent fits to MR
images.
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89. | Chalana, V, Winter, TC, Cyr, DR, Haynor, DR, and Kim, YM, "Automatic fetal head measurements from sonographic images," ACADEMIC RADIOLOGY, vol. 3, pp. 628-635, 1996.
Abstract:
Rationale and Objectives. We designed an image processing technique to
automatically measure the biparietal diameter (BPD) and head
circumference (HC) from prenatal sonograms, We evaluated the
performance of the algorithm by comparing the resulting measurements
with those made by experienced sonographers.
Methods. Thirty-five digitized sonograms of the fetal head were
obtained during routine imaging, The BPD and HC were automatically
computed by detecting the inner and outer boundaries of the fetal skull
using the computer vision technique known as the ''active contour
model.'' Six experienced sonographers also measured the BPD and HC on
these images.
Results. The algorithm failed to locate the boundaries in two of the 35
cases. For the remaining cases, the mean absolute difference betnieen
the automated measurements and the average of the six observers was
1.4% for BPD and 2.9% for HC. The correlations were .999 for the BPD
and .994 for the HC. The computer's measurements were no different from
the six observers' measurements than the observers' measurements were
from one another.
Conclusion. The tested algorithm effectively and accurately measures
BPD and HC automatically. We are currently in the process of
integrating this algorithm into an ultrasound machine.
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90. | Yang, ZY, "Nonlinear superposition of receptive fields and phase transitions," PHYSICS LETTERS A, vol. 219, pp. 277-281, 1996.
Abstract:
We present a principle of nonlinear superposition of receptive fields.
Changes of connection weight, applied field or the distances between
the input centers can lead to a new phase with all neurons encoding
certain shapes excited. This process is a kind of phase transition and
can be used for information processing.
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91. | Dow, AI, Shafer, SA, Kirkwood, JM, Mascari, RA, and Waggoner, AS, "Automatic multiparameter fluorescence imaging for determining lymphocyte phenotype and activation status in melanoma tissue sections," CYTOMETRY, vol. 25, pp. 71-81, 1996.
Abstract:
A system has been developed that combines multiparameter fluorescence
imaging and computer vision techniques to provide automatic phenotyping
of multiple cell types in a single tissue section. This system
identifies both the nuclear and cytoplasmic boundary of each cell. A
routine based on the watershed algorithm has been developed to segment
an image of Hoechst-stained nuclei with an accuracy of greater than
85%. Deformable splines initially positioned at the nuclear boundaries
are applied to images of fluorescently labelled cell-surface antigens.
The splines lock onto the peak fluorescence signal surrounding the
cell, providing an estimate of the cell boundary. From measurements
acquired at this boundary, each cell is classified according to antigen
expression.
The system has been piloted in biopsies from melanoma patients
participating in a clinical trial of the antibody R(24). Thin tissue
sections have been stained with Hoechst and three different fluorescent
antibodies to antigens that permit the typing and evaluation of
activity of T-cells. Changes in the infiltrates evaluated by
multiparameter imaging were consistent with results obtained by
immunoperoxidase analysis. The multiparameter fluorescent technique
enables simultaneous determination of multiple cell subsets and can
provide the spatial relationships of each cell type within the tissue.
(C) 1996 Wiley-Liss, Inc.
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92. | Bulpitt, AJ, and Efford, ND, "An efficient 3D deformable model with a self-optimising mesh," IMAGE AND VISION COMPUTING, vol. 14, pp. 573-580, 1996.
Abstract:
Deformable models are a powerful and popular tool for image
segmentation, but in 3D imaging applications the high computational
cost of fitting such models can be a problem. A further drawback is the
need to select the initial size and position of a model in such a way
that it is close to the desired solution. This task may require
particular expertise on the part of the operator, and, furthermore, may
be difficult to accomplish in three dimensions without the use of
sophisticated visualisation techniques. This article describes a 3D
deformable model that uses an adaptive mesh to increase computational
efficiency and accuracy. The model employs a distance transform in
order to overcome some of the problems caused by inaccurate
initialisation. The performance of the model is illustrated by its
application to the task of segmentation of 3D MR images of the human
head and hand. A quantitative analysis of the performance is also
provided using a synthetic test image.
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93. | Ip, HHS, and Yu, RPK, "Recursive splitting of active contours in multiple clump segmentation," ELECTRONICS LETTERS, vol. 32, pp. 1564-1566, 1996.
Abstract:
A new technique is presented for clump decomposition based on the
recursive splitting of active contours. The approach does not require
prior knowledge of tlx number of objects and the sizes of the objects
to be segmented.
|
94. | Nesi, P, and Magnolfi, R, "Tracking and synthesizing facial motions with dynamic contours," REAL-TIME IMAGING, vol. 2, pp. 67-79, 1996.
Abstract:
Many researchers have studied techniques related to the analysis and
synthesis of human heads under motion with face deformations. These
techniques can be used for defining low-rate Image compression
algorithms (model-based image coding), cinema technologies,
videophones, as well as for applications of virtual reality, etc. Such
techniques need a real-time performance and a strong integration
between the mechanisms of motion estimation and those of rendering and
animation of the 3D synthetic head/face. In this paper, a complete and
integrated system for tracking and synthesizing facial motions in
real-time with low-cost architectures is presented. Facial deformations
curves represented as spatiotemporal B-splines are used for tracking in
order to model the main facial features. In addition, the system
proposed is capable of adapting a generic 3D wire-frame model of a
head/face to the face that must be tracked; therefore: the simulations
of the face deformations are produced by using a realistic patterned
face. (C) 1996 Academic Press Limited
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95. | Beylot, P, Gingins, P, Kalra, P, Thalmann, NM, Maurel, W, Thalmann, D, and Fasel, J, "3D interactive topological modeling using visible human dataset," COMPUTER GRAPHICS FORUM, vol. 15, pp. C33-&, 1996.
Abstract:
Availability of Visible Human Dataset (VHD) has provided numerous
possibilities for its exploitation bl both medical applications and 3D
animation. In this paper, we present our interactive tools which enable
extraction of surfaces for different organs, including bones, muscles,
fascia, and skin, from the VHD. The reconstructed surfaces then are
used for defining the inter-relationship of organs, a process bye refer
to as topological modeling. A data base is constructed, which
encapsulates structural, topological, mechanical and other relevant
information about organs. A 3D interactive tool enables the building
and editing of this data base. Such a data base can later be used for
different applications in fields such as medicine, sports, education,
and entertainment.
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96. | Berger, MO, Chevrier, C, and Simon, G, "Compositing computer and video image sequences: Robust algorithms for the reconstruction of the camera parameters," COMPUTER GRAPHICS FORUM, vol. 15, pp. C23-&, 1996.
Abstract:
Augmented reality shows great promises in fields where a simulation in
situ would be impossible or too expensive. When mixing synthetic and
real objects in the same animated sequence, we must be sure that the
geometrical coherence as well as the photometrical coherence is
ensured. One major challenge is to compute the camera viewpoint with
sufficient accuracy to ensure a satisfactory composition. We especially
address this point in this paper using computer vision techniques and
robust statistical methods. We prove that such techniques make it
possible to compute almost automatically the viewpoint for long video
sequences even for bad quality images in outdoor environments.
Significant results on the lighting simulation of the bridges of Paris
are shown.
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97. | Mason, DC, and Davenport, IJ, "Accurate and efficient determination of the shoreline in ERS-1 SAR images," IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 34, pp. 1243-1253, 1996.
Abstract:
Extraction of the shoreline in SAR images is a difficult task to
perform using simple image processing operations such as grey-value
thresholding, due to the presence of speckle and because the signal
returned from the sea surface may be similar to that from the land. A
semiautomatic method for detecting the shoreline accurately and
efficiently in ERS-1 SAR images is presented. This is aimed primarily
at a particular application; namely the construction of a digital
elevation model of an intertidal zone using SAR images and hydrodynamic
model output, but could be carried over to other applications. A
coarse-fine resolution processing approach is employed, in which sea
regions are first detected as regions of low edge density in a low
resolution image, then image areas near the shoreline are subjected to
more elaborate processing at high resolution using an active contour
model. Over 90% of the shoreline detected by the automatic delineation
process appear visually correct.
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98. | Lejeune, A, and Ferrie, FP, "Finding the parts of objects in range images," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 64, pp. 230-247, 1996.
Abstract:
A key problem in the interpretation of visual form is the partitioning
of a shape into components that correspond to the parts of an object.
This paper presents a method for partitioning a set of surface
estimates obtained with a laser range finding system into subsets
corresponding to such parts. Parts are defined implicitly by means of a
feature set that identifies putative part boundaries that have been
computed by external means. The strategy employed makes use of two
complementary representations for surfaces: one that describes local
structures in terms of differential properties (e.g., edges, lines,
contours) and the other that represents the surface as a collection of
smooth patches at different scales. It is shown that by enforcing a
consistent interpretation between these two representations, it is
possible to derive a partitioning algorithm that is both efficient and
robust. Examples of its performance on a set of range images are
presented. (C) 1996 Academic Press, Inc.
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99. | Cramer, C, Gelenbe, E, and Bakircioglu, H, "Low bit-rate video compression with neural networks and temporal subsampling," PROCEEDINGS OF THE IEEE, vol. 84, pp. 1529-1543, 1996.
Abstract:
Image and video compression is becoming an increasingly important area
of investigation, with numerous applications to video conferencing,
interactive education, home entertainment, and potential applications
to earth observation, medical imaging, digital libraries, and many
other areas. In this paper we describe a novel neural network technique
for video compression, using a ''point-process'' type neural network
model we have developed [1]-[4] which is closer to biophysical reality
and is mathematically much more tractable than standard models. Our
algorithm uses an adaptive approach based upon the users' desired video
quality Q, and achieves compression ratios of up to 500:1 for moving
gray-scale images, based on a combination of motion detection,
compression ratio of over 1000:1 for full-color video sequences with
the addition of the standard 4:1:1 spatial subsampling ratios in the
chrominance images. The signal-to-noise ratio (SNR) obtained varies
with the compression level and ranges from 29 dB to over 34 dB. Our
method is computationally fast so that compression and decompression
could possibly be preformed in real-time software. Compression is
preformed using a combination of motion detection, neural networks, and
temporal subsampling of frames. A set of neural networks is used to
adaptively select the desired compression of each picture block as a
function of the reconstruction quality. The motion detection process
separates out regions of the frame which need to be retransmitted.
Temporal subsampling of frames, along with reconstruction technique,
lead to the high compression ratios reported in this paper.
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100. | Tannenbaum, A, "Three snippets of curve evolution theory in computer vision," MATHEMATICAL AND COMPUTER MODELLING, vol. 24, pp. 103-119, 1996.
Abstract:
In this paper, we discuss some uses of curve evolution theory for
problems in computer vision. We concentrate on three problem areas:
shape theory, active contours, and geometric invariant scale spaces.
The solutions to these key problems will all be based on flows which
are obtained in a completely natural manner from geometric and physical
principles.
|
101. | Olstad, B, and Torp, AH, "Encoding of a priori information in active contour models," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 18, pp. 863-872, 1996.
Abstract:
The theory of active contours models the problem of contour recovery as
an energy minimization process. The computational solutions based on
dynamic programming require that the energy associated with a contour
candidate can be decomposed into an integral of local energy
contributions. In this paper we propose a grammatical framework that
can model different local energy models and a set of allowable
transitions between these models. The grammatical encodings are
utilized to represent a priori knowledge about the shape of the object
and the associated signatures in the underlying images. The variability
encountered in numerical experiments is addressed with the energy
minimization procedure which is embedded in the grammatical framework.
We propose an algorithmic solution that combines a nondeterministic
version of the Knuth-Morris-Pratt algorithm for string matching with a
time-delayed discrete dynamic programming algorithm for energy
minimization. The numerical experiments address practical problems
encountered in contour recovery such as noise robustness and occlusion.
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102. | Staib, LH, and Duncan, JS, "Model-based deformable surface finding for medical images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 720-731, 1996.
Abstract:
This paper describes a new global shape parameterization for smoothly
deformable three-dimensional (3-D) objects, such as those found in
biomedical images, whose diversity and irregularity make them difficult
to represent in terms of fixed features or parts. This representation
is used for geometric surface matching to 3-D medical image data, such
as from magnetic resonance imaging (MRI). The parameterization
decomposes the surface into sinusoidal basis functions. Four types of
surfaces are modeled: tori, open surfaces, closed surfaces and tubes.
This parameterization allows a wide variety of smooth surfaces to be
described with a small number of parameters. Extrinsic model-based
information is incorporated by introducing prior probabilities on the
parameters. Surface finding is formulated as an optimization problem,
Results of the method applied to synthetic images and 3-D medical
images of the heart and brain are presented.
|
103. | Wang, G, Snyder, DL, OSullivan, JA, and Vannier, MW, "Iterative deblurring for CT metal artifact reduction," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 657-664, 1996.
Abstract:
Iterative deblurring methods using the expectation maximization (EM)
formulation and the algebraic reconstruction technique (ART),
respectively, are adapted for metal artifact reduction in medical
computed tomography (CT). In experiments with synthetic noise-free and
additive noisy projection data of dental phantoms, it is found that
both simultaneous iterative algorithms produce superior image quality
as compared to filtered backprojection after linearly fitting
projection gaps. Furthermore, the EM-type algorithm converges faster
than the ART-type algorithm in terms of either the I-divergence or
Euclidean distance between ideal and reprojected data in our
simulation. Also, for a given iteration number, the EM-type deblurring
method produces better image clarity but stronger noise than the
ART-type reconstruction. The computational complexity of EM- and
ART-based iterative deblurring is essentially the same, dominated by
reprojection and backprojection. Relevant practical and theoretical
issues are discussed.
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104. | Hutchinson, S, Hager, GD, and Corke, PI, "A tutorial on visual servo control," IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, vol. 12, pp. 651-670, 1996.
Abstract:
This article provides a tutorial introduction to visual servo control
of robotic manipulators, Since the topic spans many disciplines our
goal is limited to providing a basic conceptual framework, We begin by
reviewing the prerequisite topics from robotics and computer vision,
including a brief review of coordinate transformations, velocity
representation, and a description of the geometric aspects of the image
formation process, We then present a taxonomy of visual servo control
systems, The two major classes of systems, position-based and
image-based systems, are then discussed in detail, Since any visual
servo system must be capable of tracking image features in a sequence
of images, we also include an overview of feature-based and
correlation-based methods for tracking, We conclude the tutorial with a
number of observations on the current directions of the research field
of visual servo control.
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105. | Kichenassamy, S, Kumar, A, Olver, P, Tannenbaum, A, and Yezzi, A, "Conformal curvature flows: From phase transitions to active vision," ARCHIVE FOR RATIONAL MECHANICS AND ANALYSIS, vol. 134, pp. 275-301, 1996.
Abstract:
In this paper, we analyze geometric active contour models from a curve
evolution point of view and propose some modifications based on
gradient flows relative to certain new feature-based Riemannian
metrics. This leads to a novel edge-detection paradigm in which the
feature of interest may be considered to lie at the bottom of a
potential well. Thus an edge-seeking curve is attracted very naturally
and efficiently to the desired feature. Comparison with the Allen-Cahn
model clarifies some of the choices made in these models, and suggests
inhomogeneous models which may in return be useful in phase
transitions. We also consider some 3-dimensional active surface models
based on these ideas. The justification of this model rests on the
careful study of the viscosity solutions of evolution equations derived
from a level-set approach.
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106. | Denzler, J, and Niemann, H, "3D data driven prediction for active contour models based on geometric bounding volumes," PATTERN RECOGNITION LETTERS, vol. 17, pp. 1171-1178, 1996.
Abstract:
Active contour models have proven to be a promising approach for data
driven object tracking without knowledge about the problem domain and
the object. Problems arise in case of fast moving objects and in
natural scenes with heterogeneous background. In these cases, a
prediction step is an essential part of the tracking mechanism.
In this paper we describe a new approach for modelling the contour of
moving objects in the 3D world. The key point is the description of
moving objects by a simplified geometric model, the sc-called bounding
volume. The contour of moving objects is predicted by estimating the
movement and the shape of the bounding volume in the 3D world and by
projecting its contour to the image plane. Stochastic optimization
algorithms are used to estimate shape parameters of the bounding
volume. The 2D contour of the bounding volume is used to initialize the
active contour, which then extracts the contour of the moving object.
Thus, an update of the motion and model parameters of the bounding
volume is possible. No task specific knowledge and no a priori
knowledge about the object is necessary. We will show that in the case
of convex polyhedral bounding volumes, this method can be applied to
real-time closed-loop object tracking on standard Unix workstations.
Furthermore, we present experiments which prove that the robustness for
tracking moving objects in front of a heterogeneous background can be
improved.
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107. | Couvignou, PA, Papanikolopoulos, NP, Sullivan, M, and Khosla, PK, "The use of active deformable models in model-based robotic visual servoing," JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, vol. 17, pp. 195-221, 1996.
Abstract:
This paper presents a new approach for visual tracking and servoing in
robotics. We introduce deformable active models as a powerful means for
tracking a rigid or semi-rigid (possibly partially occluded) object in
movement within the manipulator's workspace. Deformable models imitate,
in real-time, the dynamic behavior of elastic structures. These
computer-generated models are designed to capture the silhouette of
objects with well-defined boundaries, in terms of image gradient. By
means of an eye-in-hand robot arm configuration, the desired motion of
the end-effector is computed with the objective of keeping the target's
position and shape invariant with respect to the camera frame. Optimal
estimation and control techniques (LQG regulator) have been
successfully implemented in order to deal with noisy measurements
provided by our vision sensor. Experimental results are presented for
the tracking of a rigid or semi-rigid object. The experiments performed
in a real-time environment show the effectiveness and robustness of the
proposed method for servoing tasks based on visual feedback.
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108. | Yan, RH, Tokuda, N, and Miyamichi, J, "A model-based active landmarks tracking method," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E79D, pp. 1477-1482, 1996.
Abstract:
Unlike The time-consuming contour tracking method of snakes [5] which
requires a considerable number of iterated computations before contours
are successfully tracked down, we present a faster and accurate
model-based ''landmarks'' tracking method where a single iteration of
the dynamic programming is sufficient to obtain a local minimum to an
integral measure of the elastic and the image energy functionals. The
key lies in choosing a relatively small number of salient
''landmarks'', or features of objects, rather than their contours as a
target of tracking within the image structure. The landmarks comprising
singular points along the model contours are tracked down within the
image structure all inside restricted search areas of 41 x 41 pixels
whose respective locations in image structure are dictated by their
locations in the model. A Manhattan distance and a template corner
detection function of Singh and Shneier [7] are used as elastic energy
and image energy respectively in the algorithm. A first approximation
to the image contour is obtained in our method by applying the
thin-plate spline transformation of Bookstein [2] using these landmarks
as fixed points of the transformation which is capable of preserving a
global shape information of the model including the relative
configuration of landmarks and consequently surrounding contours of the
model in the image structure. The actual image contours are further
tracked down by applying an active edge tracker using now simplified
line search segments so that individual differences persisting between
the mapped model contour are substantially eliminated. We have applied
our method tentatively to portraits of a class album to demonstrate the
effectiveness of the method. Our experiments convincingly show that
using only about 11 feature points our method provides not only a much
improved computational complexity requiring only 0.94 sec. in CPU time
by SGI's indigo2 but also more accurate shape representations than
those obtained by the snakes methods. The method is powerful in a
problem domain where the model-based approach is applicable, possibly
allowing real time processing because a most time consuming algorithm
of corner template evaluation can be easily implemented by parallel
processing firmware.
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109. | Huang, TS, Stroming, JW, Kang, Y, and Lopez, R, "Advances in very low bit rate video coding in North America," IEICE TRANSACTIONS ON COMMUNICATIONS, vol. E79B, pp. 1425-1433, 1996.
Abstract:
Research in very low-bit rate coding has made significant advancements
in the past few years. Most recently, the introduction of the MPEG-4
proposal has motivated a wide variety of approaches aimed al achieving
a new level of video compression. In this paper we review progress in
VLBV categorized into 3 main areas: (1) Waveform coding, (2) 2D
Content-based coding, and (3) Model-based coding. Where appropriate we
also described proposals to the MPEG-4 committee in each of these areas.
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110. | Germain, O, and Refregier, P, "Optimal snake-based segmentation of a random luminance target on a spatially disjoint background," OPTICS LETTERS, vol. 21, pp. 1845-1847, 1996.
Abstract:
We describe a segmentation processor that is optimal for tracking the
shape of a target with random white Gaussian intensity appearing on a
random white Gaussian spatially disjoint background. This algorithm,
based on an active contours model (snakes), consists of correlations of
binary reference's with preprocessed versions of the scene image. This
result can provide a practical method to adapt the reference image to
correlation techniques. (C) 1996 Optical Society of America
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111. | Wang, M, Evans, J, Hassebrook, L, and Knapp, C, "A multistage, optimal active contour model," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 5, pp. 1586-1591, 1996.
Abstract:
Energy-minimizing active contour models or snakes can be used in many
applications such as edge detection, motion tracking, image matching,
computer vision, and three-dimensional (3-D) reconstruction. We present
a novel snake that is superior both in accuracy and convergence speed
over previous snake algorithms. High performance is achieved by using
spline representation and dividing the energy-minimization process into
multiple stages. The first stage is designed to optimize the
convergence speed in order to allow the snake to quickly approach the
minimum-energy state. The second stage is devoted to snake refinement
and to local minimization of energy, thereby driving the snake to a
quasiminimum-energy state. The third stage uses the Bellman optimality
principle to fine-tune the snake to the global minimum-energy state.
This three-stage scheme is optimized for both accuracy and speed.
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112. | Malladi, R, and Sethian, JA, "A unified approach to noise removal, image enhancement, and shape recovery," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 5, pp. 1554-1568, 1996.
Abstract:
We present a unified approach to noise removal, image enhancement, and
shape recovery in images. The underlying approach relies on the level
set formulation of curve and surface motion, which leads to a class of
PDE-based algorithms. Beginning with an image, the first stage of this
approach removes noise and enhances the image by evolving the image
under flow controlled by min/max curvature and by the mean curvature.
This stage is applicable to both salt-and-pepper grey-scale noise and
full-image continuous noise present in black and white images,
grey-scale images, texture images, and color images. The noise
removal/enhancement schemes applied in this stage contain only one
enhancement parameter, which in most cases is automatically chosen. The
other key advantage of our approach is that a stopping criteria is
automatically picked from the image; continued application of the
scheme produces no further change. The second stage of our approach is
the shape recovery of a desired object; we again exploit the level set
approach to evolve an initial curve/surface toward the desired
boundary, driven by an image-dependent speed function that
automatically stops at the desired boundary.
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113. | Smith, CE, Richards, CA, Brandt, SA, and Papanikolopoulos, NP, "Visual tracking for intelligent vehicle-highway systems," IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 45, pp. 744-759, 1996.
Abstract:
The complexity and congestion of current transportation systems often
produce traffic situations that jeopardize the safety of the people
involved, These situations vary from maintaining a safe distance behind
a leading vehicle to safely allowing a pedestrian to cross a busy
street. Environmental sensing plays a critical role in virtually all of
these situations, Of the sensors available, vision sensors protide
information that Is richer and more complete than other sensors, making
them a logical choice for a multisensor transportation system, In this
paper we propose robust detection and tracking techniques for
intelligent vehicle-highway applications where computer vision plays a
crucial role, In particular, se demonstrate that the Controlled Active
Vision framework [15] can be utilized to provide a visual tracking
modality to a traffic advisory system in order to increase the overall
safety margin in a variety bf common traffic situations, We have
selected two application examples. vehicle tracking and pedestrian
tracking, to demonstrate that the framework fan provide precisely the
type of information required to effectively manage the given traffic
situation.
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114. | Nastar, C, and Ayache, N, "Frequency-based nonrigid motion analysis: Application to four dimensional medical images," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 18, pp. 1067-1079, 1996.
Abstract:
We present a method for nonrigid motion analysis in time sequences of
volume images (4D data). In this method, nonrigid motion of the
deforming object contour is dynamically approximated by a
physically-based deformable surface. In order to reduce the number of
parameters describing the deformation, we make use of a modal analysis
which provides a spatial smoothing of the surface. The deformation
spectrum, which outlines the main excited modes, can be efficiently
used for deformation comparison. Fourier analysis on time signals of
the main deformation spectrum components provides a temporal smoothing
of the data. Thus a complex nonrigid deformation is described by only a
few parameters: the main excited modes and the main Fourier harmonics.
Therefore, 4D data can be analyzed in a very concise manner. The power
and robustness of the approach is illustrated by various results on
medical data. We believe that our method has important applications in
automatic diagnosis of heart diseases and in motion compression.
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115. | Lee, JD, "Genetic approach to select wavelet features for contour extraction in medical ultrasonic imaging," ELECTRONICS LETTERS, vol. 32, pp. 2137-2138, 1996.
Abstract:
An efficient and robust approach, which is based on wavelet transform
(WT), is proposed to contour extraction for medical ultrasonic images
having low signal-to-noise ratio. Furthermore, the best wavelet
features for profile analysis is estimated by GAs without manual
operation. No image preprocessing is needed, so computation time is
fast. Experimental results to confirm the proposed algorithm are also
included.
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116. | Laprie, Y, and Berger, MO, "Cooperation of regularization and speech heuristics to control automatic formant tracking," SPEECH COMMUNICATION, vol. 19, pp. 255-269, 1996.
Abstract:
This paper describes an automatic formant tracking algorithm
incorporating speech knowledge. It operates in two phases. The first
detects and interprets spectrogram peak lines in terms of formants. The
second uses an image contour extraction method to regularise the peak
lines thus detected. Speech knowledge served as acoustic constraints to
guide the interpretation of peak lines. The proposed algorithm has the
advantage of providing formant trajectories which, in addition to being
sufficiently close to the spectral peaks of the respective formants,
are sufficiently smooth to allow an accurate evaluation of formant
transitions. The results obtained highlight the interest of the
proposed approach.
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117. | Maurer, CR, Aboutanos, GB, Dawant, BM, Maciunas, RJ, and Fitzpatrick, JM, "Registration of 3-D images using weighted geometrical features," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 836-849, 1996.
Abstract:
In this paper, we present a weighted geometrical feature (WGF)
registration algorithm. Its efficacy is demonstrated by combining
points and a surface. The technique is an extension of Besl and McKay's
iterative closest point (ICP) algorithm. We use the WGF algorithm to
register X-ray computed tomography (CT) and T2-weighted magnetic
resonance (MR) volume head images acquired from eleven patients that
underwent craniotomies in a neurosurgical clinical trial. Each patient
had five external markers attached to transcutaneous posts screwed into
the outer table of the skull. We define registration error as the
distance between positions of corresponding markers that are not used
for registration. The CT and MR images are registered using fiducial
points (marker positions) only, a surface only, and various weighted
combinations of points and a surface. The CT surface is derived from
contours corresponding to the inner surface of the skull. The MR
surface is derived front contours corresponding to the cerebrospinal
fluid (CSF)-dura interface. Registration using points and a surface is
found to be significantly more accurate than registration using only
points or a surface.
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118. | Davatzikos, C, and Bryan, RN, "Using a deformable surface model to obtain a shape representation of the cortex," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 785-795, 1996.
Abstract:
This paper examines the problem of obtaining a mathematical
representation of the outer cortex of the human brain, which is a key
problem in several applications, including morphological analysis of
the brain, and spatial normalization and registration of brain images.
A parameterization of the outer cortex is first obtained using a
deformable surface algorithm which, motivated by the structure of the
cortex, is constructed to find the central layer of thick surfaces.
Based on this parameterization, a hierarchical representation of the
outer cortical structure is proposed through its depth map and its
curvature maps at various scales. Various experiments on magnetic
resonance data are presented.
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119. | Toklu, C, Erdem, AT, Sezan, MI, and Tekalp, AM, "Tracking motion and intensity variations using hierarchical 2-D mesh modeling for synthetic object transfiguration," GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 58, pp. 553-573, 1996.
Abstract:
We propose a method for tracking the motion and intensity variations of
a 2-D mildly deformable image object using a hierarchical 2-D mesh
model. The proposed method is applied to synthetic object
transfiguration, namely, replacing an object in a real video clip with
another synthetic or natural object via digital postprocessing.
Successful transfiguration requires accurate tracking of both motion
and intensity (contrast and brightness) variations of the
object-to-be-replaced so that the replacement object can be rendered in
exactly the same way from a single still picture. The proposed method
is capable of tracking image regions corresponding to scene objects
with nonplanar and/or mildly deforming surfaces, accounting for
intensity variations, and is shown to be effective with real image
sequences. (C) 1996 Academic Press, Inc.
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120. | Demongeot, J, and Leitner, F, "Compact set valued flows .1. Applications in medical imaging," COMPTES RENDUS DE L ACADEMIE DES SCIENCES SERIE II FASCICULE B-MECANIQUE PHYSIQUE CHIMIE ASTRONOMIE, vol. 323, pp. 747-754, 1996.
Abstract:
Compact set valued dynamical systems have a large field of applications
in image processing and morphogenesis modelling. In section 2 of this
paper, we will define the notion of compact set valued Row. In section
3, we will propose some examples of potential Rows used in 3D-image
contouring. In section 4, we will introduce the notion of mixed
potential-hamiltonian flows, which could be used in 4D-image
contouring, which generalizes the 2D potential-hamiltonian contouring
method. Finally, in section 5 we will give a simple example of compact
set valued iterations, and in section 6 an example of distribution tube
iterations.
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121. | Kita, Y, "Elastic-model driven analysis of several views of a deformable cylindrical object," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 18, pp. 1150-1162, 1996.
Abstract:
This paper proposes a method to extract regions of a deformable object
from several views of it while finding the correspondence of the object
among the views. The method has been developed to analyze X-ray images
of a stomach. Owing to the physical (not physiological) deformation oi
the stomach and changes of the camera angle, the shape oi the stomach
regions are fairly different among the Images. In order to collectively
analyze these images, we use an elastic stomach model. Firstly, our
method builds an elastic stomach model based on the stomach shape in
one image. Considering each photographing condition, the deformation of
the stomach in each image is simulated with the elastic model.
Referring to the predicted contour which is obtained by projecting the
deformed model from the camera angle of each image, the contour is
robustly extracted from noisy images in a model-driven way. Since the
predicted contour registered in each image corresponds with the elastic
model, the position of each stomach part in the image is simultaneously
obtained; corresponding parts can be found among the images through the
model. Experimental results of analyzing several types of stomach X-ray
images are shown and discussed.
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122. | Lee, S, Wolberg, G, Chwa, KY, and Shin, SY, "Image metamorphosis with scattered feature constraints," IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, vol. 2, pp. 337-354, 1996.
Abstract:
This paper describes an image metamorphosis technique to handle
scattered feature constraints specified with points, polylines, and
splines. Solutions to the following three problems are presented:
feature specification, warp generation, and transition control. We
demonstrate the use of snakes to reduce the burden of feature
specification. Next, we propose the use of multilevel free-form
deformations (MFFD) to compute C-2-continuous and one-to-one mapping
functions among the specified features. The resulting technique, based
on B-spline approximation, is simpler and faster than previous warp
generation methods. Furthermore, it produces smooth image
transformations without undesirable ripples and foldovers. Finally, we
simplify the MFFD algorithm to derive transition functions to control
geometry and color blending. Implementation details are furnished and
comparisons among Various metamorphosis techniques are presented.
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123. | Irrgang, R, and Irrgang, H, "An intelligent snake growing algorithm for fuzzy shape detection," EXPERT SYSTEMS WITH APPLICATIONS, vol. 11, pp. 531-536, 1996.
Abstract:
A novel, robust algorithm for connectivity detection in the shape
recognition process has been developed. The algorithm is a simplified
version of the snake or active contour technique for object boundary
detection. Access to a case base and constraint system is available at
all stages of the process which increases the probability that
semantically meaningful objects will be detected. The technique has
proved valuable for a number of applications from the aerospace
industry including shape recognition and fatigue crack detection. The
algorithm has also been used to generate an improved version of the
STIRS technique for shape recognition. Copyright (C) 1996 Elsevier
Science Ltd
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124. | Sato, K, Sugawara, K, Narita, Y, and Namura, I, "Consideration of the method of image diagnosis with respect to frontal lobe atrophy," IEEE TRANSACTIONS ON NUCLEAR SCIENCE, vol. 43, pp. 3230-3239, 1996.
Abstract:
This paper proposes a segmentation method for a quantitative image
diagnosis as a means of realizing an objective diagnosis of the frontal
lobe atrophy, From the data obtained on the grade of membership, the
fractal dimensions of the cerebral tissue [cerebral spinal fluid (CSF),
gray matter, and white matter] and the contours are estimated, The
mutual relationship between the degree of atrophy and the fractal
dimension has been analyzed based on the estimated fractal dimensions,
Using a sample of 42 male and Female cases, ranging in age from 50's to
70's, it has been concluded that the frontal lobe atrophy can be
quantified by regarding it as an expansion of CSF region on the
magnetic resonance imaging (MRI) of the brain, Furthermore, when the
process of frontal lobe atrophy is separated into early and advanced
stages, the volumetric change of CSF and white matter in frontal lobe
displays meaningful differences between the two stages, demonstrating
that the fractal dimension of CSF rises with the progress of atrophy,
Moreover, an interpolation method for three-dimensional (3-D) shape
reconstruction of the region of diagnostic interest is proposed and 3-D
shape visualization, with respect to the degree and form of atrophy, is
performed on the basis of the estimated fractal dimension of the
segmented cerebral tissue.
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125. | Atkins, MS, and Mackiewich, BT, "Automatic segmentation of the brain in MRI," VISUALIZATION IN BIOMEDICAL COMPUTING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1131, pp. 241-246, 1996.
Abstract:
This paper describes a robust fully automatic method for segmenting the
brain from head MR images, which works even in the presence of RF
inhomogeneities. It has been successful in segmenting the brain in
every slice from head images acquired from three different MRI
scanners, using different resolution images and different echo
sequences. The three-stage integrated method employs image processing
techniques based on anisotropic filters, ''snakes'' contouring
techniques, and a-priori knowledge. First the background noise is
removed leaving a head mask, then a rough outline of the brain is
found, and finally the rough brain outline is refined to a final mask.
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126. | Kelemen, A, Szekely, G, Reist, HW, and Gerig, G, "Automatic segmentation of cell nuclei from confocal laser scanning microscopy images," VISUALIZATION IN BIOMEDICAL COMPUTING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1131, pp. 193-202, 1996.
Abstract:
In this paper we present a method for the fully automatic segmentation
of cell nuclei from 3D confocal laser microscopy images. The method is
based on the combination of previously proposed techniques which have
been refined for the requirements of this task. A 3D extension of a
wave propagation technique applied to gradient magnitude images allows
us a precise initialization of elastically deformable Fourier models
and therefore a fully automatic image analysis. The shape parameters
are transformed into invariant descriptors and provide the basis of a
statistical analysis of cell nucleus shapes. This analysis will be
carried out in order to determine average intersection lengths between
cell nuclei and single particle tracks of ionizing radiation. This
allows a quantification of absorbed energy on living cells leading to a
better understanding of the biological significance of exposure to
radiation in low doses.
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127. | McAuliffe, MJ, Eberly, D, Fritsch, DS, Chaney, EL, and Pizer, SM, "Scale-space boundary evolution initialized by cores," VISUALIZATION IN BIOMEDICAL COMPUTING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1131, pp. 173-182, 1996.
Abstract:
A novel interactive segmentation method has been developed which uses
estimated boundaries, generated from cores, to initialize a scale-space
boundary evolution process in greyscale medical images. Presented is an
important addition to core extraction methodology that improves core
generation for objects that are in the presence of interfering objects.
The boundary at the scale of the core (BASOC) and its associated width
information, both derived from the core, are used to initialize the
second stage of the segmentation process. In this automatic refinement
stage, the BASOC is allowed to evolve in a spline-snake-like manner
that makes use of object-relevant width information to make robust
measurements of local edge positions.
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128. | Masutani, Y, Masamune, K, and Dohi, T, "Region-growing based feature extraction algorithm for tree-like objects," VISUALIZATION IN BIOMEDICAL COMPUTING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1131, pp. 161-171, 1996.
Abstract:
To overcome limitations of the conventional 'toward-axis' voxel-removal
way of thinning operations, a new 'along-axis' style of algorithm was
developed for topological information acquisition of tree-like objects
like vascular shapes based on region-growing technique. The theory of
mathematical morphology is extended for closed space inside binary
shapes, and the 'closed space dilation' operation is introduced as
generalized form of region growing. Using synthetic and clinical 3D
images, its superior features, such as parametric controllability were
shown.
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129. | Rogowska, J, Batchelder, K, Gazelle, GS, Halpern, EF, Connor, W, and Wolf, GL, "Evaluation of selected two-dimensional segmentation techniques for computed tomography quantitation of lymph nodes," INVESTIGATIVE RADIOLOGY, vol. 31, pp. 138-145, 1996.
Abstract:
RATIONALE AND OBJECTIVES. AS contrast agents that selectively target
normal lymph nodes are undergoing development and evaluation, it has
become important to accurately and reproducibly determine nodal
boundaries to study. the agents and determine such values as lymph node
area or mean nodal contrast concentration. This study was performed to
evaluate the accuracy of different two-dimensional computer
segmentation methods, tested on acrylic phantoms constructed to imitate
the appearance of lymph nodes surrounded bg fat.
METHODS. Five segmentation techniques (manual tracing, semiautomatic
local criteria threshold selection, Sobel/watershed technique,
interactive deformable contour algorithm and thresholding) were
evaluated using phantoms, Subsequently, the first three methods were
applied to the images of enhanced lymph nodes in rabbits.
RESULTS. Minimum errors in phantom area measurement (<5%) and
interoperator variation (<5%) were seen with the Sobel/watershed
technique and the interactive deformable contour algorithm, These two
techniques were significantly better than thresholding and
semiautomated thresholding based on local properties.
CONCLUSION. Methods based on Sobel edge detection offer more objective
tools than thresholding methods for segmenting objects similar to lymph
nodes in computed tomography images, Both methods, Sobel/watershed and
interactive deformable contour algorithm, are fast and have simple user
interfaces.
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130. | Carlsson, S, "Projectively invariant decomposition and recognition of planar shapes," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 17, pp. 193-209, 1996.
Abstract:
An algorithm is presented for computing a decomposition of planar
shapes into convex subparts represented by ellipses, The method is
invariant to projective transformations of the shape, and thus the
conic primitives can be used for matching and definition of invariants
in the same way as points and lines. The method works for arbitrary
planar shapes admitting at least four distinct tangents and it is based
on finding ellipses with four points of contact to the given shape. The
cross ratio computed from the four points on the ellipse can then be
used as a projectively invariant index. It is demonstrated that a given
shape has a unique parameter-free decomposition into a finite set of
ellipses with unit cross ratio. For a given shape, each pair of
ellipses can be used to compute two independent projective invariants.
The set of invariants computed for each ellipse pair can be used as
indexes to a hash table from which model hypothesis can be generated
Examples of shape decomposition and recognition are given for synthetic
shapes and shapes extracted from grey level images of real objects
using edge detection.
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131. | Worring, M, Smeulders, AWM, Staib, LH, and Duncan, JS, "Parameterized feasible boundaries in gradient vector fields," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 63, pp. 135-144, 1996.
Abstract:
Segmentation of(noisy) images containing a complex ensemble of objects
is difficult to achieve on the basis of local image information only.
It is advantageous to attack the problem of object boundary extraction
by a model-based segmentation procedure, Segmentation is achieved by
tuning the parameters of the geometrical model in such a way that the
boundary template locates and describes the object in the image in an
optimal way, The optimality of the solution is based on an objective
function taking into account image information as well as the shape of
the template. Objective functions in literature are mainly based on the
gradient magnitude and a measure describing the smoothness of the
template. In this contribution, we propose a new image objective
function based on directional gradient information derived from
Gaussian smoothed derivatives of the image data, The proposed method is
designed to accurately locate an object boundary even in the case of a
conflicting object positioned close to the object of interest, We
further introduce a new smoothness objective to ensure the physical
feasibility of the contour. The method is evaluated on artificial data,
Results on real medical images show that the method is very effective
in accurately locating object boundaries in very complex images. (C)
1996 Academic Press, Inc.
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132. | Alpert, NM, Berdichevsky, D, Levin, Z, Morris, ED, and Fischman, AJ, "Improved methods for image registration," NEUROIMAGE, vol. 3, pp. 10-18, 1996.
Abstract:
We report a system for PET-MRI registration that is improved or
optimized in several areas: (1) Automatic scalp/brain segmentation
replaces manual drawing operations, (2) a new fast and accurate method
of image registration, (3) visual assessment of registration quality is
enhanced by composite imaging methods (i.e., fusion) and (4) the entire
procedure is embedded in a commercially available scientific
visualization package, thereby providing a consistent graphical user
interface. The segmentation algorithm was tested on 17 MRI data sets
and was successful in all cases. Accuracy of image registration was
equal to that of the Woods algorithm, but 10 times faster for PET-PET
and 4 times faster for PET-MRI. The image fusion method allows
detection of misalignments on the order of 2-3 mm. These results
demonstrate an integrated system for intermodality image registration,
which is important because the procedure can be performed by
technicians with no anatomic knowledge and reduces the required time
from hours to about 15 min on a modern computer workstation. (C) 1996
Academic Press, Inc.
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133. | Tai, YC, Lin, KP, Dahlbom, M, and Hoffman, EJ, "A hybrid attenuation correction technique to compensate for lung density in 3-D total body PET," IEEE TRANSACTIONS ON NUCLEAR SCIENCE, vol. 43, pp. 323-330, 1996.
Abstract:
A hybrid attenuation correction technique (ACT) is under development
for F-18-FDG total body positron emission tomography (PET). With a
short transmission scan of the thorax, any time within a few days of
the imaging session, this technique can correct for attenuation in the
entire body, Segmentation, registration, and active contour finding
techniques are applied to both emission and short transmission images
to locate and map the major attenuating structures in the body. This
technique eliminates the need for the patient to remain still from the
start of the transmission scan to the end of the emission scan without
the added noise of simultaneous or post emission transmission scan
measurements, The results of volunteer studies are comparable to
standard measured ACT, both visually and quantitatively, The efficient
use of scanner time and improved patient comfort make this technique
particularly suitable for clinical imaging.
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134. | Chuang, GCH, and Kuo, CCJ, "Wavelet descriptor of planar curves: Theory and applications," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 5, pp. 56-70, 1996.
Abstract:
By using the wavelet transform, we develop a hierarchical planar curve
descriptor that decomposes a curve into components of different scales
so that the coarsest scale components carry the global approximation
information while the finer scale components contain the local detailed
information, We show that the wavelet descriptor has many desirable
properties such as multiresolution representation, invariance,
uniqueness, stability, and spatial localization, A deformable wavelet
descriptor is also proposed by interpreting the wavelet coefficients as
random variables, The applications of the wavelet descriptor to
character recognition and model-based contour extraction from low SNR
images are examined, Numerical experiments are performed to illustrate
the performance of the wavelet descriptor.
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135. | Krishnamachari, S, and Chellappa, R, "Delineating buildings by grouping lines with MRFs," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 5, pp. 164-168, 1996.
Abstract:
Traditionally, Markov random field (MRF) models have been used in
low-level image analysis. This correspondence presents an MRF-based
scheme to perform object delineation. The proposed edge-based approach
involves extracting straight lines from the edge map of an image. Then,
an MRF model is used to group these lines to delineate buildings in
aerial images.
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136. | Davatzikos, C, Vaillant, M, Resnick, SM, Prince, JL, Letovsky, S, and Bryan, RN, "A computerized approach for morphological analysis of the corpus callosum," JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, vol. 20, pp. 88-97, 1996.
Abstract:
Objective: A new technique for analyzing the morphology of the corpus
callosum is presented, and it is applied to a group of elderly subjects.
Materials and Methods: The proposed approach normalizes subject data
into the Talairach space using an elastic deformation transformation.
The properties of this transformation are used as a quantitative
description of the callosal shape with respect to the Talairach atlas,
which is treated as a standard. In particular, a deformation function
measures the enlargement/shrinkage associated with this elastic
deformation. Intersubject comparisons are made by comparing deformation
functions.
Results: This technique was applied to eight male and eight female
subjects. Based on the average deformation functions of each group, the
posterior region of the female corpus callosum was found to be larger
than its corresponding region in the males. The average callosal shape
of each group was also found, demonstrating visually the callosal shape
differences between the two groups in this sample.
Conclusion: The proposed methodology utilizes the full resolution of
the data, rather than relying on global descriptions such as area
measurements. The application of this methodology to an elderly group
indicated sex-related differences in the callosal shape and size.
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137. | Yang, QS, and Marchant, JA, "Accurate blemish detection with active contour models," COMPUTERS AND ELECTRONICS IN AGRICULTURE, vol. 14, pp. 77-89, 1996.
Abstract:
This paper presents a novel image analysis scheme for accurate
detection of fruit blemishes. The detection procedure consists of two
steps: initial segmentation and refinement. In the first step,
blemishes are coarsely segmented out with a flooding algorithm and in
the second step an active contour model, i.e. a snake algorithm, is
applied to refine the segmentation so that the localization and size
accuracy of detected blemishes is improved. The concept and the
formulation of the snake algorithm are briefly introduced and then the
refinement procedure is described. The initial tests for sample apple
images have shown very promising results.
|
138. | Fishman, EK, Kuszyk, BS, Heath, DG, Gao, LM, and Cabral, B, "Surgical planning for liver resection," COMPUTER, vol. 29, pp. 64-&, 1996.
Abstract:
Effective surgical planning requires 3D images that show tumor location
relative to key blood vessels. This research uses volume rendering of
CT data to meet these requirements.
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139. | Kent, JT, Mardia, KV, and Walder, AN, "Conditional cyclic Markov random fields," ADVANCES IN APPLIED PROBABILITY, vol. 28, pp. 1-12, 1996.
Abstract:
Grenander et al. (1991) proposed a conditional cyclic Gaussian Markov
random field model for the edges of a closed outline in the plane. In
this paper the model is recast as an improper cyclic Gaussian Markov
random field for the vertices. The limiting behaviour of this model
when the vertices become closely spaced is also described and in
particular its relationship with the theory of 'snakes' (Kass et al.
1987) is established. Applications are given in Grenander et al.
(1991), Mardia el al. (1991) and Kent et al. (1992).
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140. | Taubin, G, and Ronfard, R, "Implicit simplicial models for adaptive curve reconstruction," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 18, pp. 321-325, 1996.
Abstract:
Parametric deformable models have been extensively and very
successfully used for reconstructing free-form curves and surfaces, and
for tracking nonrigid deformations, but they require previous knowledge
of the topological type of the data, and good initial curve or surface
estimates. With deformable models, it is also computationally expensive
to check for and to prevent self-intersections while tracking
deformations. The Implicit Simplicial Models that we introduce in this
paper are implicit curves and surfaces defined by piece-wise linear
functions. This representation allows for local deformations, control
of the topological type, and prevention of self-intersections during
deformations. As a first application, we also describe in this paper an
algorithm for two-dimensional curve reconstruction from unorganized
sets of data points. The topology, the number of connected components,
and the geometry of the data are all estimated using an adaptive space
subdivision approach. The main four components of the algorithm are
topology estimation, curve fitting, adaptive space subdivision, and
mesh relaxation.
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141. | Jolly, MPD, Lakshmanan, S, and Jain, AK, "Vehicle segmentation and classification using deformable templates," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 18, pp. 293-308, 1996.
Abstract:
This paper proposes a segmentation algorithm using deformable template
models to segment a vehicle of interest both from the stationary
complex background and other moving vehicles in an image sequence. We
define a polygonal template to characterize a general model of a
vehicle and derive a prior probability density function to constrain
the template to be deformed within a set of allowed shapes. We propose
a likelihood probability density function which combines motion
information and edge directionality to ensure that the deformable
template is contained within the moving areas in the image and its
boundary coincides with strong edges with the same orientation in the
image. The segmentation problem is reduced to a minimization problem
and solved by the Metropolis algorithm. The system was successfully
tested on 405 image sequences containing multiple moving vehicles on a
highway.
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142. | Jain, AK, Zhong, Y, and Lakshmanan, S, "Object matching using deformable templates," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 18, pp. 267-278, 1996.
Abstract:
We propose a general object localization and retrieval scheme based on
object shape using deformable templates. Prior knowledge of an object
shape is described by a prototype template which consists of the
representative contour/edges, and a set of probabilistic deformation
transformations on the template. A Bayesian scheme, which is based on
this prior knowledge and the edge information in the input image, is
employed to find a match between the deformed template and objects in
the image. Computational efficiency is achieved via a coarse-to-fine
implementation of the matching algorithm. Our method has been applied
to retrieve objects with a variety of shapes from images with complex
background. The proposed scheme is invariant to location, rotation, and
moderate scale changes of the template.
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143. | Carstensen, JM, "An active lattice model in a Bayesian framework," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 63, pp. 380-387, 1996.
Abstract:
A Markov Random Field is used as a structural model of a deformable
rectangular lattice. When used as a template prior in a Bayesian
framework this model is powerful for making inferences about lattice
structures in images, The model assigns maximum probability to the
perfect regular lattice by penalizing deviations in alignment and
lattice node distance, The Markov random field represents prior
knowledge about the lattice structure, and through an observation model
that incorporates the visual appearance of the nodes, we can simulate
realizations from the posterior distribution. A maximum a posteriori
(MAP) estimate, found by simulated annealing, is used as the
reconstructed lattice. The model was developed as a central part of an
algorithm for automatic analysis of genetic experiments, positioned in
a lattice structure by a robot. The algorithm has been successfully
applied to many images, and it seems to be a fast, accurate, and robust
solution to the problem. Several possible extensions of the model are
described. (C) 1996 Academic Press, Inc.
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144. | Robert, L, "Camera calibration without feature extraction," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 63, pp. 314-325, 1996.
Abstract:
This paper presents an original approach to the problem of camera
calibration using a calibration pattern, It consists of directly
searching for the camera parameters that best project three-dimensional
points of a calibration pattern onto intensity edges in an image of
this pattern, without explicitly extracting the edges. Based on a
characterization of image edges as maxima of the intensity gradient or
zero-crossings of the Laplacian, we express the whole calibration
process as a one-stage optimization problem. A classical iterative
optimization technique is used in order to solve it. Our approach is
different from the classical calibration techniques which involve two
consecutive stages: extraction of image features and computation of the
camera parameters. Thus, our approach is easier to implement and to
use, less dependent on the type of calibration pattern that is used,
and more robust. First, we describe the details of the approach, Then,
we show some experiments in which two implementations of our approach
and two classical two-stage approaches are compared, Tests on real and
synthetic data allow us to characterize our approach in terms of
convergence, sensitivity to the initial conditions, reliability, and
accuracy. (C) 1996 Academic Press, Inc.
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145. | Trier, OD, Jain, AK, and Taxt, T, "Feature extraction methods for character recognition - A survey," PATTERN RECOGNITION, vol. 29, pp. 641-662, 1996.
Abstract:
This paper presents an overview of feature extraction methods for
off-line recognition of segmented (isolated) characters. Selection of a
feature extraction method is probably the single most important factor
in achieving high recognition performance in character recognition
systems. Different feature extraction methods are designed for
different representations df the characters, such as solid binary
characters, character contours, skeletons (thinned characters) or
gray-level subimages of each individual character. The feature
extraction methods are discussed in terms of invariance properties,
reconstructability and expected distortions and variability of the
characters. The problem of choosing the appropriate feature extraction
method for a given application is also discussed. When a few promising
feature extraction methods have been identified, they need to be
evaluated experimentally to find the best method for the given
application.
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146. | Lam, KM, and Yan, H, "Locating and extracting the eye in human face images," PATTERN RECOGNITION, vol. 29, pp. 771-779, 1996.
Abstract:
Facial feature extraction is an important step in automated visual
interpretation and human face recognition. Among the facial features,
the eye plays the most important part in the recognition process. The
deformable template can be used in extracting the eye boundaries.
However, the weaknesses of the deformable template are that the
processing time is lengthy and that its success relies on the initial
position of the template. in this paper, the head boundary is first
located in a head-and-shoulders image. The approximate positions of the
eyes are estimated by means of average anthropometric measures.
Corners, the salient features of the eyes, are detected and used to set
the initial parameters of the eye templates. The corner detection
scheme introduced in this paper can provide accurate information about
the corners. Based on the corner positions, we can accurately locate
the templates in relation to the eye images and greatly reduce the
processing time for the templates. The performance of the deformable
template is assessed with and without using the information on corner
positions. Experiments show that a saving in execution time of about
40% on average and a better eye boundary representation can be achieved
by using the corner information.
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147. | Kraitchman, DL, Wilke, N, Hexeberg, E, JeroschHerold, M, Wang, Y, Parrish, TB, Chang, CN, Zhang, Y, Bache, RJ, and Axel, L, "Myocardial perfusion and function in dogs with moderate coronary stenosis," MAGNETIC RESONANCE IN MEDICINE, vol. 35, pp. 771-780, 1996.
Abstract:
MRI studies of first-pass contrast enhancement with polylysine-Gd-DTPA
and myocardial tagging using spatial modulation of magnetization
(SPAMM) were performed to assess the feasibility of a combined regional
myocardial blood flow and 2D deformation exam, Instrumented
closed-chest dogs were imaged at a baseline control state (Cntl)
followed by two interventions: moderate coronary stenosis (St) achieved
by partial occlusion of the left anterior descending (LAD) and moderate
coronary stenosis with dobutamine loading (StD), Hypoperfusion of the
anterior region (ANT) of the myocardium (LAD distribution) relative to
the posterior wall (POS) based on the upslope of the signal intensity
time curve from the contrast-enhanced MR images was demonstrated only
with dobutamine loading (ANT:POS Cntl = 1.077 +/- 0.15 versus ANT:POS
StD = 0.477 +/- 0.11, P < 0.03) and was confirmed with radiolabeled
microspheres measurements (ANT:POS Cntl = 1.18 +/- 0.2 ml/min/g versus
ANT:POS StD = 0.44 +/- 0.1 ml/min/g; P < 0.002). Significant changes in
regional myocardial shortening were only seen in the StD state (P <
0.02); the anterior region showed impaired myocardial shortening with
dobutamine loading (P = NS), whereas the nonaffected POS region showed
a marked increase in shortening when compared with Cntl (Cntl = 0.964
+/- 0.02 versus StD = 0.884 +/- 0.03; P < 0.001). These results
demonstrate that an integrated quantitative assessment of regional
myocardial function and semiquantitative assessment of myocardial blood
flow can be performed noninvasively with ultrafast MRI.
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148. | Helterbrand, JD, "One-pixel-wide closed boundary identification," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 5, pp. 780-783, 1996.
Abstract:
An appropriate space of one-pixel-wide closed (OPWC) boundary
configurations is explicitly defined and an automatic algorithm to
obtain OPWC contour estimates from a segmented image is presented. The
motivation is to obtain a reasonable starting estimate for a Markov
chain Monte Carlo-based (McMC-based) boundary optimization algorithm.
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149. | Yuen, PC, Wong, YY, and Tong, CS, "Contour detection using enhanced snakes algorithm," ELECTRONICS LETTERS, vol. 32, pp. 202-204, 1996.
Abstract:
An enhanced snakes algorithm (ESA) for detecting object contours is
designed and developed. In the ESA, a novel split and merge technique
is added to the original snakes model to enhance the model to support
the detection of concave object contours. A set of handtools is
selected to evaluate the proposed algorithm, and the results are
encouraging.
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150. | Chalana, V, Linker, DT, Haynor, DR, and Kim, YM, "A multiple active contour model for cardiac boundary detection on echocardiographic sequences," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 15, pp. 290-298, 1996.
Abstract:
Tracing of left-ventricular epicardial and endocardial borders on
echocardiographic sequences is essential for quantification of cardiac
function. We designed a method based on an extension of active contour
models to detect both epicardial and endocardial borders on short-axis
cardiac sequences spanning the entire cardiac cycle, We validated the
results by comparing the computer-generated boundaries to the
boundaries manually outlined by four expert observers on 44 clinical
data sets, The mean boundary distance between the computer-generated
boundaries and the manually outlined boundaries was 2.80 mm (sigma =
1.28 mm) for the epicardium and 3.61 (sigma = 1.68 mm) for the
endocardium, These distances were comparable to interobserver
distances, which had a mean of 3.79 mm (sigma = 1.53 mm) for epicardial
borders and 2.67 mm (sigma = 0.88 mm) for endocardial borders, The
correlation coefficient between the areas enclosed by the
computer-generated boundaries and the average manually outlined
boundaries was 0.95 for epicardium and 0.91 for endocardium, The
algorithm is fairly insensitive to the choice of the initial curve,
Thus, we have developed an effective and robust algorithm to extract
left-ventricular boundaries from echocardiographic sequences.
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151. | Hoch, M, and Litwinowicz, PC, "A semi-automatic system for edge tracking with snakes," VISUAL COMPUTER, vol. 12, pp. 75-83, 1996.
Abstract:
Active contour models, or ''snakes,'' developed in (Kass et al. 1988),
use a simple physical model to track edges in image sequences. Snakes
as originally defined however, tend to shrink, stretch and slide back
and forth in unwanted ways along a tracked edge and are also confused
by multiple edges, always grabbing the nearest one. In this paper a
semi-automatic system is presented that combines motion estimation
techniques with snakes to overcome these problems. An algorithm is
presented that uses a block matching technique to guide the endpoints
of the snake, optical flow to push the snake in the direction of the
underlying motion, followed by the traditional snake edge-fitting
minimization process. We use this technique for tracking facial
features of an actor for driving computer animated characters.
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1997 |
152. | Zhou, P, and Pycock, D, "Robust statistical models for cell image interpretation," IMAGE AND VISION COMPUTING, vol. 15, pp. 307-316, 1997.
Abstract:
A robust and adaptable model-based scheme for cell image interpretation
is presented that can accommodate the wide natural variation in the
appearance of cells. This is achieved using multiple models and an
interpretation process that permits a smooth transition between models.
Boundaries are represented using trainable statistical models that are
invariant to transformations of scaling, shift, rotation and contrast;
a Gaussian and a circular autoregressive (CAR) model are investigated.
The interpretation process optimises the match between models and data
using a Bayesian distance measure. We demonstrate how objects that vary
in both shape and grey-level pattern can reliably be segmented. The
results presented show that overall performance is comparable with that
for manual segmentation; the area within the automatically and manually
selected cell boundaries that is not common to both is less than 5% in
96% of the cases tested. The results also show that the computationally
simpler Gaussian boundary model is at least as effective as the CAR
model.
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153. | Androutsos, D, Trahanias, PE, and Venetsanopoulos, AN, "Application of active contours for photochromic tracer flow extraction," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 284-293, 1997.
Abstract:
This paper addresses the implementation of image processing and
computer vision techniques to automate tracer flow extraction in images
obtained by the photochromic dye technique. This task is important in
modeled arterial blood flow studies. Currently, it is performed via
manual application of B-spline curve fitting. However, this is a
tedious and error-prone procedure and its results are nonreproducible,
In the proposed approach, active contours, snakes, are employed in a
new curve-fitting method for tracer flow extraction in photochromic
images. An algorithm implementing snakes is introduced to automate
extraction, Utilizing correlation matching, the algorithm quickly
locates and localizes all flow traces in the images. The feasibility of
the method for tracer flow extraction is demonstrated. Moreover,
results regarding the automation algorithm are presented showing its
accuracy and effectiveness. The proposed approach for tracer flow
extraction has potential for real-system application.
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154. | Boyer, E, and Berger, MO, "3D surface reconstruction using occluding contours," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 22, pp. 219-233, 1997.
Abstract:
This paper addresses the problem of 3D surface reconstruction using
image sequences. It has been shown that shape recovery from three or
more occluding contours of the surface is possible given a known camera
motion. Several algorithms, which have been recently proposed, allow
such a reconstruction under the assumption of a linear camera motion. A
new approach is presented which deals with the reconstruction problem
directly from a discrete point of view. First, a theoretical study of
the epipolar correspondence between occluding contours is achieved. A
correct depth formulation is then derived from a local approximation of
the surface up to order two. This allows the local shape to be
estimated, given three consecutive contours, without any constraints on
the camera motion. Experimental results are presented for both
synthetic and real data.
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155. | Szeliski, R, and Coughlan, J, "Spline-based image registration," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 22, pp. 199-218, 1997.
Abstract:
The problem of image registration subsumes a number of problems and
techniques in multiframe image analysis, including the computation of
optic flow (general pixel-based motion), stereo correspondence,
structure from motion, and feature tracking. We present a new
registration algorithm based on spline representations of the
displacement field which can be specialized to solve all of the above
mentioned problems. In particular, we show how to compute local flow,
global (parametric) flow, rigid flow resulting from camera egomotion,
and multiframe versions of the above problems. Using a spline-based
description of the flow removes the need for overlapping correlation
windows, and produces an explicit measure of the correlation between
adjacent flow estimates. We demonstrate our algorithm on multiframe
image registration and the recovery of 3D projective scene geometry.
mie also provide results on a number of standard motion sequences.
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156. | Lai, SH, and Vemuri, BC, "Physically based adaptive preconditioning for early vision," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 594-607, 1997.
Abstract:
Several problems in early vision have been formulated in the past in a
regularization framework. These problems, when discretized, lead to
large sparse linear systems. In this paper, we present a novel
physically based adaptive preconditioning technique which can be used
in conjunction with a conjugate gradient algorithm to dramatically
improve the speed of convergence for solving the aforementioned linear
systems. A preconditioner, based on the membrane spline, or the thin
plate spline, or a convex combination of the two, is termed a
physically based preconditioner for obvious reasons. The adaptation of
the preconditioner to an early vision problem is achieved via the
explicit use of the spectral characteristics of the regularization
filter in conjunction with the data. This spectral function is used to
modulate the frequency characteristics of a chosen wavelet basis, and
these modulated values are then used in the construction of our
preconditioner. We present the preconditioner construction for three
different early vision problems namely, the surface reconstruction, the
shape from shading, and the optical flow computation problems.
Performance of the preconditioning scheme is demonstrated via
experiments on synthetic and real data sets. We note that our
preconditioner outperforms other methods of preconditioning for these
early vision problems, described in computer Vision literature.
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157. | Richards, CA, and Papanikolopoulos, NP, "Detection and tracking for robotic visual servoing systems," ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, vol. 13, pp. 101-120, 1997.
Abstract:
Robot manipulators require knowledge about their environment in order
to perform their desired actions. In several robotic tasks, vision
sensors play a critical role by providing the necessary quantity and
quality of information regarding the robot's environment. For example,
''visual servoing'' algorithms may control a robot manipulator in order
to track moving objects that are being imaged by a camera. Current
visual servoing systems often lack the ability to detect automatically
objects that appear within the camera's field of view. In this
research, we present a robust ''figure/ground'' framework for visually
detecting objects of interest. An important contribution of this
research is a collection of optimization schemes that allow tbe
detection framework to operate within the real-time Limits of visual
servoing systems. The most significant of these schemes involves the
use of ''spontaneous'' and ''continuous'' domains. The number and
location of continuous domains are,allowed to change over time,
adjusting to the dynamic conditions of the detection process. We have
developed actual servoing systems in order to test the framework's
feasibility and to demonstrate its usefulness for visually controlling
a robot manipulator. (C) 1997 Elsevier Science Ltd.
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158. | Hamza, R, Zhang, XDD, Macosko, CW, Steve, R, and Listemann, M, "Imaging open-cell polyurethane foam via confocal microscopy," POLYMERIC FOAMS, ACS SYMPOSIUM SERIES, vol. 669, pp. 165-177, 1997.
Abstract:
Flexible polyurethane foam is based on a 3-dimensional cellular
network. The mechanical properties of foam material depend upon cell
structure and cell size distribution. In this work, we use laser
confocal microscopy to image the foam cells and recover its
3-dimensional cellular network. Based on this technique we provide a
statistical analysis and compare several foam samples. Confocal
microscopic images are also used to visualize foam compression. Images
for foam network structure under different mechanical compressions are
also obtained. Limitations of confocal microscope are discussed and a
new method - nuclear magnetic resonance imaging is proposed.
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159. | Smyth, PP, Taylor, CJ, and Adams, JE, "Automatic measurement of vertebral shape using active shape models," IMAGE AND VISION COMPUTING, vol. 15, pp. 575-581, 1997.
Abstract:
In this paper, we describe how Active Shape Models (ASMs) have been
used to accurately and robustly locate vertebrae in lateral Dual Energy
X-ray Absorptiometry (DXA) images of the spine. DXA images are of low
spatial resolution, and contain significant random and structural
noise, providing a difficult challenge for object location methods. All
vertebrae in the image were searched for simultaneously, improving
robustness in location of individual vertebrae by making use of
constraints on shape provided by the position of other vertebrae. We
show that the use of ASMs with minimal user interaction allows accuracy
to be obtained which is as good as that achievable by human operators,
as well as high precision. Having located each vertebra, it is
desirable to evaluate whether it has been located sufficiently
accurately for shape measurements to be useful. We determined this on
the basis of grey-level model fit, which was shown to usefully detect
poorly located vertebrae, which should enable accuracy to be improved
by rejecting proposed search solutions whose grey-level fit was poorer
than a threshold. (C) 1997 Elsevier Science B.V.
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160. | Pathak, SD, Chalana, V, and Kim, YM, "Interactive automatic fetal head measurements from ultrasound images using multimedia computer technology," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 23, pp. 665-673, 1997.
Abstract:
We have developed a tool to automatically detect inner and outer skull
boundaries of a fetal head in ultrasound images, These boundaries are
used to measure biparietal diameter (BPD) and head circumference (HC).
The algorithm is based on active contour models and takes 32 s on a Sun
SparcStation 20/71, A high-performance desktop multimedia system called
MediaStation 5000 (MS5000) is used as a model for our future ultrasound
subsystem, On the MS5000, the optimized implementation of this
algorithm takes 248 ms, The difference (between the computer-measured
values on MS5000 and the gold standard) for BPD and HC was 1.43% (sigma
= 1,00%) and 1.96% (sigma = 1.96%), respectively. According to our data
analysis, no significant differences exist in the BPD and HC
measurements made on the MS5000 and those measurements made on the Sun
SparcStation 20/71, Reduction in the overall execution time from 32 s
to 248 ms will help making this algorithm a practical ultrasound tool
for sonographers, (C) 1997 World Federation for Ultrasound in Medicine
and Biology.
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161. | Chiou, GI, and Hwang, JN, "Lipreading from color video," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 6, pp. 1192-1195, 1997.
Abstract:
We have designed and implemented a lipreading system that recognizes
isolated words using only color video of human lips (without acoustic
data). The system performs video recognition using ''snakes'' to
extract visual features of geometric space, Karhunen-Loeve transform
(KLT) to extract principal components in the color eigenspace, and
hidden Markov models (HMM's) to recognize the combined visual features
sequences. With the visual information alone, we were able to achieve
94% accuracy for ten isolated words.
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162. | Moghaddam, B, and Pentland, A, "Probabilistic visual learning for object representation," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 696-710, 1997.
Abstract:
We present an unsupervised technique for visual learning, which is
based on density estimation in high-dimensional spaces using an
eigenspace decomposition. Two types of density estimates are derived
for modeling the training data: a multivariate Gaussian (for unimodal
distributions) and a Mixture-of-Gaussians model (for multimodal
distributions). These probability densities are then used to formulate
a maximum-likelihood estimation framework for visual search and target
detection for automatic object recognition and coding. Our learning
technique is applied to the probabilistic visual modeling, detection,
recognition, and coding of human faces and nonrigid objects, such as
hands.
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163. | Gruen, A, and Li, HH, "Semi-automatic linear feature extraction by dynamic programming and LSB-Snakes," PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, vol. 63, pp. 985-995, 1997.
Abstract:
This paper deals with semi-automatic linear feature extraction from
digital images for GIS data capture, where the identification task is
performed manually on a single image, while a special automatic digital
module performs the high precision feature tracking in two-dimensional
(2-D) image space or even three-dimensional (3-D) object space. A human
operator identifies the object from an on-screen display of a digital
image, selects the particular class this object belongs to, and
provides a very few coarsely distributed seed points. Subsequently,
with these seed points as an approximation of the position and shape,
the linear feature will be extracted automatically by either a dynamic
programming approach or by LSB-Snakes (Least-Squares B-spline Snakes).
With dynamic programming, the optimization problem is set up as a
discrete multistage decision process and is solved by a time delayed''
algorithm. It ensures global optimality, is numerically stable, and
allows for hard constraints to be enforced on the solution. In the
least-squares approach, we combine three types of observation
equations, one radiometric, formulating the matching of a generic
object model with image data, and two that express the internal
geometric constraints of a curve and the location of operator-given
seed points. The solution is obtained by solving a pair of independent
normal equations to estimate the parameters of the spline curve. Both
techniques can be used in a monoplotting mode, which combines one image
with its underlying DTM. The LSB-Snakes approach is also implemented in
a multi-image mode, which uses multiple images simultaneously and
provides for a robust and mathematically sound full 3D approach. These
techniques are not restricted to aerial images. They can be applied to
satellite and close-range images as well. The issues related to the
mathematical modeling of the proposed methods are discussed and
experimental results are shown in this paper too.
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164. | Kollnig, H, and Nagel, HM, "3D pose estimation by directly matching polyhedral models to gray value gradients," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 23, pp. 283-302, 1997.
Abstract:
This contribution addresses the problem of pose estimation and tracking
of vehicles in image sequences from traffic scenes recorded by a
stationary camera. In a new algorithm, the vehicle pose is estimated by
directly matching polyhedral vehicle models to image gradients without
an edge segment extraction process. The new approach is significantly
more robust than approaches that rely on feature extraction since the
new approach exploits more information from the image data. We
successfully tracked vehicles that were partially occluded by textured
objects, e.g., foliage, where a previous approach based on edge segment
extraction failed. Moreover, the new pose estimation approach is also
used to determine the orientation and position of the road relative to
the camera by matching an intersection model directly to image
gradients. Results from various experiments with real world traffic
scenes are presented.
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165. | Ashton, EA, Parker, KJ, Berg, MJ, and Chen, CW, "A novel volumetric feature extraction technique with applications to MR images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 365-371, 1997.
Abstract:
A semiautomated feature extraction algorithm is presented for the
extraction and measurement of the hippocampus from volumetric magnetic
resonance imaging (MRI) head scans. This algorithm makes use of
elements of both deformable model and region growing techniques and
allows incorporation of a priori operator knowledge of hippocampal
location and shape, Experimental results indicate that the algorithm is
able to estimate hippocampal volume and asymmetry with an accuracy
which approaches that of laborious manual outlining techniques.
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166. | Wolberg, WH, Street, WN, and Mangasarian, OL, "Computer-derived nuclear features compared with axillary lymph node status for breast carcinoma prognosis," CANCER CYTOPATHOLOGY, vol. 81, pp. 172-179, 1997.
Abstract:
BACKGROUND. Both axillary lymph node involvement and tumor anaplasia,
as expressed by visually assessed grade, have been shown to be
prognostically important in breast carcinoma outcome. In this study,
axillary lymph node involvement was used as the standard against which
prognostic estimations based on computer-derived nuclear features were
gauged,
METHODS, The prognostic significance of nuclear morphometric features
determined by computer-based image analysis were analyzed in 198
consecutive preop preoperative samples obtained by fine-needle
aspiration (FNA) from patients with invasive breast carcinoma. A novel
multivariate prediction method was used to model the time of distant
recurrence as a function of the nuclear features. Prognostic
predictions based on the nuclear feature data were cross-validated to
avoid overly optimistic conclusions. The estimated accuracy of these
prognostic determinations was compared with determinations based on the
extent of axillary lymph node involvement.
RESULTS. The predicted outcomes based on nuclear features were divided
into three groups representing best, intermediate, and worst prognosis,
and compared with the traditional TNM lymph node stratification.
Nuclear feature stratification better separated the prognostically best
from the intermediate group whereas lymph node stratification better
separated the prognostically intermediate from the worst group.
Prognostic accuracy was not increased by adding lymph node status or
tumor size to the nuclear features.
CONCLUSIONS. Computer analysis of a preoperative FNA more accurately
identified prognostically favorable patients than did pathologic
examination of axillary lymph nodes and may obviate the need for
routine axillary lymph node dissection. (C) 1997 American Cancer
Society.
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167. | March, R, and Dozio, M, "A variational method for the recovery of smooth boundaries," IMAGE AND VISION COMPUTING, vol. 15, pp. 705-712, 1997.
Abstract:
Variational methods for image segmentation try to recover a piecewise
smooth function together with a discontinuity set which represents the
boundaries of the segmentation. This paper deals with a variational
method that constrains the formation of discontinuities along smooth
contours. The functional to be minimized, which involves the
computation of the geometrical properties of the boundaries, is
approximated by a sequence of functionals which can be discretized in a
straightforward way. Computer examples of real images are presented to
illustrate the feasibility of the method. (C) 1997 Elsevier Science B.V.
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168. | Whaite, P, and Ferrie, FP, "On the sequential determination of model misfit," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 899-905, 1997.
Abstract:
Many strategies in computer vision assume the existence of general
purpose models that can be used to characterize a scene or environment
at various levels of abstraction. The usual assumptions are that a
selected model is competent to describe a particular attribute and that
the parameters of this model can be estimated by interpreting the input
data in an appropriate manner (e.g., location of lines and edges,
segmentation into parts or regions, etc.). This paper considers the
problem of how to determine when those assumptions break down. The
traditional approach is to use statistical misfit measures based on an
assumed sensor noise model. The problem is that correct operation often
depends critically on the correctness of the noise model. Instead, we
show how this can be accomplished with a minimum of a priori knowledge
and within the framework of an active approach which builds a
description of environment structure and noise over several viewpoints.
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169. | Taylor, CJ, Cootes, TF, Lanitis, A, Edwards, G, Smyth, P, and Kotcheff, ACW, "Model-based interpretation of complex and variable images," PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES, vol. 352, pp. 1267-1274, 1997.
Abstract:
The ultimate goal of machine vision is image understanding-the ability
not only to recover image structure but also to know what it
represents. By definition, this involves the use of models which
describe and label the expected structure of the world. Over the past
decade, model-based vision has been applied successfully to images of
man-made objects. It has proved much more difficult to develop
model-based approaches to the interpretation of images of complex and
variable structures such as faces or the internal organs of the human
body (as visualized in medical images). In such cases it has been
problematic even to recover image structure reliably without a model to
organize the often noisy and incomplete image evidence. The key problem
is that of variability. To be useful, a model needs to be specific-that
is, to be capable of representing only 'legal' examples of the modelled
object(s). It has proved difficult to achieve this whilst allowing for
natural variability. Recent developments have overcome this problem; it
has been shown that specific patterns of variability in shape and
grey-level appearance can be captured by statistical models that can be
used directly in image interpretation. The details of the approach are
outlined and practical examples from medical image interpretation and
face recognition are used to illustrate how previously intractable
problems can now be tackled successfully. It is also interesting to ask
whether these results provide any possible insights into natural
vision; for example, we show that the apparent changes in shape which
result from viewing three-dimensional objects from different viewpoints
can be modelled quite well in two dimensions; this may lend some
support to the 'characteristic views' model of natural vision.
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170. | Cohen, LD, and Kimmel, R, "Global minimum for active contour models: A minimal path approach," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 24, pp. 57-78, 1997.
Abstract:
A new boundary detection approach for shape modeling is presented. It
detects the global minimum of an active contour model's energy between
two end points. Initialization is made easier and the curve is not
trapped at a local minimum by spurious edges. We modify the ''snake''
energy by including the internal regularization term in the external
potential term. Our method is based on finding a path of minimal length
in a Riemannian metric. We then make use of a new efficient numerical
method to find this shortest path.
It is shown that the proposed energy, though based only on a potential
integrated along the curve, imposes a regularization effect like
snakes. We explore the relation between the maximum curvature along the
resulting contour and the potential generated from the image.
The method is capable to close contours, given only one point on the
objects' boundary by using a topology-based saddle search routine.
We show examples of our method applied to real aerial and medical
images.
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171. | Poon, CS, and Braun, M, "Image segmentation by a deformable contour model incorporating region analysis," PHYSICS IN MEDICINE AND BIOLOGY, vol. 42, pp. 1833-1841, 1997.
Abstract:
Deformable contour models are useful tools for image segmentation.
However, many models depend mainly on local edge-based image features
to guide the convergence of the contour. This makes the models
sensitive to noise and the initial estimate. Our model incorporates
region-based image features to improve its convergence and to reduce
its dependence on initial estimation. Computational efficiency is
achieved by an optimization strategy, modified from the greedy
algorithm of Williams and Shah. The model allows a simultaneous
optimization of multiple contours, making it useful for a large variety
of segmentation problems.
|
172. | Shih, WSV, Lin, WC, and Chen, CT, "Morphologic field morphing: Contour model-guided image interpolation," INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, vol. 8, pp. 480-490, 1997.
Abstract:
An interpolation method using contours of organs as the control
parameters is proposed to recover the intensity information in the
physical gaps of serial cross-sectional images. In our method, contour
models are used to generate the control lines required for the warping
algorithm. Contour information derived from this contour model-based
segmentation process is processed and used as the control parameters to
warp the corresponding regions in both input images into compatible
shapes. In this way, the reliability of establishing the correspondence
among different segments of the same organs is improved and the
intensity information for the interpolated intermediate slices can be
derived more faithfully, To improve the efficiency for calculating the
image warp in the field morphing process, a hierarchic decomposition
process is proposed to localize the influence of each control line
segment, In comparison with the existing intensity interpolation
algorithms that only search for corresponding points in a small
physical neighborhood, this method provides more meaningful
correspondence relationships by warping regions in images into similar
shapes before resampling to account for significant shape differences.
Several sets of experimental result are presented to show that this
method generates more realistic and less blurred interpolated images,
especially when the shape difference of corresponding contours is
significant. (C) 1997 John Wiley & Sons, Inc.
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173. | Dickinson, SJ, Christensen, HI, Tsotsos, JK, and Olofsson, G, "Active object recognition integrating attention and viewpoint control," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 67, pp. 239-260, 1997.
Abstract:
We present an active object recognition strategy which combines the use
of an attention mechanism for focusing the search for a 3D object in a
2D image, with a viewpoint control strategy for disambiguating
recovered object features. The attention mechanism consists of a
probabilistic search through a hierarchy of predicted feature
observations, taking objects into a set of regions classified according
to the shapes of their bounding contours. We motivate the use of image
regions as a focus-feature and compare their uncertainty in inferring
objects with the uncertainty of more commonly used features such as
lines or corners. If the features recovered during the attention phase
do not provide a unique mapping to the 3D object being searched, the
probabilistic feature hierarchy can be used to guide the camera to a
new viewpoint from where the object can be disambiguated. The power of
the underlying representation is its ability to unify these object
recognition behaviors within a single framework. We present the
approach in detail and evaluate its performance in the context of a
project providing robotic aids for the disabled. (C) 1997 Academic
Press.
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174. | Juhan, V, Nazarian, B, Malkani, K, Bulot, R, Bartoli, JM, and Sequeira, J, "Geometrical modelling of abdominal aortic aneurysms," CVRMED-MRCAS'97, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1205, pp. 243-252, 1997.
Abstract:
Stent graft combination devices have been developed as a new
alternative for treating abdominal aortic aneurysms. The major risk
using this new technique with standard devices is the perigraft leak.
In order to choose a suitable graft for each patient, and thus avoid
such a risk, we have developed a program which provides
three-dimensional representations of such aneurysms.
Images of abdominal regions are obtained by spiral C.T.. These images
are then transferred to a graphics workstation and processed to provide
sets of contours which represent the shape of the aorta and other
vessels. Then, a surface joining all these contours is computed; we
obtain a tree-like structure represented as a set of generalized
cylinders which are joined by means of flee-form surfaces. Such
geometrical models provide an efficient mathematical support for
further developments involving diagnosis, surgery and endoprostheses
design.
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175. | Delingette, H, "Decimation of isosurfaces with deformable models," CVRMED-MRCAS'97, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1205, pp. 83-92, 1997.
Abstract:
For many medical applications including computer-assisted surgery, it
is necessary to perform scientific computations, such as mechanical
deformation, on anatomical structure models. Such patient-based
anatomical models are often extracted from volumetric medical images as
isosurfaces. In this paper, we introduce a new algorithm for the
decimation of isosurfaces based on deformable models. The method
emphasizes the creation of mesh of high geometric and topological
properties well suited for performing scientific computation. rt allows
a close control of the distance of the mesh to the isosurface as well a
the overall smoothness of the mesh. The isosurface is stored in a
data-structure that enables the fast computation of the distance to the
isosurface. Finally, our method can handle very large datasets by
merging pieces of isosurfaces.
|
176. | Jones, TN, and Metaxas, DN, "Segmentation using deformable models with affinity-based localization," CVRMED-MRCAS'97, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1205, pp. 53-62, 1997.
Abstract:
We have developed an algorithm for segmenting objects with simple
closed curves, such as the heart and the lungs, that is independent of
the imaging modality used (e.g., MRI, CT, echocardiography). Our method
is automatic and requires as initialization a single pixel within the
boundaries of the object. Existing segmentation techniques either
require much more information during initialization, such as an
approximation to the object's boundary, or are not robust to the types
of noisy data encountered in the medical domain. By integrating
region-based and physics-based modeling techniques we have devised a
hybrid design that overcomes these limitations. In our experiments we
demonstrate that this integration automates and significantly improves
the object boundary detection results, independent of the imaging
modality used.
|
177. | McInerney, T, and Terzopoulos, D, "Medical image segmentation using topologically adaptable surfaces," CVRMED-MRCAS'97, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1205, pp. 23-32, 1997.
Abstract:
Efficient and powerful topologically adaptable deformable surfaces can
be created by embedding and defining discrete deformable surface models
in terms of an Affine Cell Decomposition (ACD) framework. The ACD
framework, combined with a novel and original reparameterization
algorithm, creates a simple but elegant mechanism for multiresolution
deformable curve, surface, and solid models to ''flow'' or ''grow''
into objects with complex geometries and topologies, and adapt their
shape to recover the object boundaries. ACD-based models maintain the
traditional parametric physics-based formulation of deformable models,
allowing them to incorporate a priori knowledge in the form of energy
and force-based constraints, and provide intuitive interactive
capabilities. This paper describes ACD-based deformable surfaces and
demonstrates their potential for extracting and reconstructing some of
the most complex biological structures from medical image volumes.
|
178. | Montagnat, J, and Delingette, H, "Volumetric medical images segmentation using shape constrained deformable models," CVRMED-MRCAS'97, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1205, pp. 13-22, 1997.
Abstract:
In this paper we address the problem of extracting geometric models
from lour contrast volumetric images, given a template or reference
shape of that model. We proceed by deforming a reference model in a
volumetric image. This reference deformable model is represented as a
simplex mesh submitted to regularizing shape constraint. Furthermore,
we introduce an original approach that combines the deformable model
framework with the elastic registration (based on iterative closest
point algorithm) method. This new method increases the robustness of
segmentation while allowing very complex deformation, of the original
template. Examples of segmentation of the liver and brain ventricles
are provided.
|
179. | Carmona, RA, Hwang, WL, and Torresani, B, "Characterization of signals by the ridges of their wavelet transforms," IEEE TRANSACTIONS ON SIGNAL PROCESSING, vol. 45, pp. 2586-2590, 1997.
Abstract:
We present a couple of new algorithmic procedures for the detection of
ridges in the modulus of the (continuous) wavelet transform of
one-dimensional (1-D) signals, These detection procedures are shown to
be robust to additive white noise, We also derive and test a new
reconstruction procedure, The latter uses only information from the
restriction of the wavelet transform to a sample of points from the
ridge. This provides a very efficient way to code the information
contained in the signal.
|
180. | Caselles, V, Kimmel, R, Sapiro, G, and Sbert, C, "Minimal surfaces: a geometric three dimensional segmentation approach," NUMERISCHE MATHEMATIK, vol. 77, pp. 423-451, 1997.
Abstract:
A novel geometric approach for three dimensional object segmentation is
presented. The scheme is based on geometric deformable surfaces moving
towards the objects to be detected, We show that this model is related
to the computation of surfaces of minimal area (local minimal
surfaces). The space where these surfaces are computed is induced from
the three dimensional image in which the objects are to be detected.
The general approach also shows the relation between classical
deformable surfaces obtained via energy minimization and geometric ones
derived from curvature flows in the surface evolution framework. The
scheme is stable, robust, and automatically handles changes in the
surface topology during the deformation. Results related to existence,
uniqueness, stability, and correctness of the solution to this
geometric deformable model are presented as well. Based on an efficient
numerical algorithm for surface evolution, we present a number of
examples of object detection in real and synthetic images.
|
181. | Axel, L, "Noninvasive measurement of cardiac strain with MRI," ANALYTICAL AND QUANTITATIVE CARDIOLOGY, ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY, vol. 430, pp. 249-256, 1997.
Abstract:
The motion sensitivity of cardiac magnetic resonance imaging (MRI) can
be exploited to measure the motion patterns within the heart wall and
thus to noninvasively calculate the intramyocardial strain. The
resulting large data sets pose a challenge for visualization, but offer
the potential of a greatly improved picture of cardiac dynamics. This
may have both basic research and clinical applications.
|
182. | Grzeszczuk, RP, and Levin, DN, "''Brownian strings'': Segmenting images with stochastically deformable contours," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 1100-1114, 1997.
Abstract:
This paper describes an image segmentation technique in which an
arbitrarily shaped contour was deformed stochastically until it fitted
around an object of interest. The evolution of the contour was
controlled by a simulated annealing process which caused the contour to
settle into the global minimum of an image-derived ''energy'' function.
The nonparametric energy function was derived from the statistical
properties of previously segmented images, thereby incorporating prior
experience. Since the method was based on a state space search for the
contour with the best global properties, it was stable in the presence
of image errors which confound segmentation techniques based on local
criteria, such as connectivity. Unlike ''snakes'' and other active
contour approaches, the new method could handle arbitrarily irregular
contours in which each interpixel crack represented an independent
degree of freedom. Furthermore, since the contour evolved toward the
global minimum of the energy, the method was more suitable for fully
automatic applications than the snake algorithm, which frequently has
to be reinitialized when the contour becomes trapped in local energy
minima. High computational complexity was avoided by efficiently
introducing a random local perturbation in a time independent of
contour length, providing control over the size of the perturbation,
and assuring that resulting shape changes were unbiased. The method was
illustrated by using it to find the brain surface in magnetic resonance
head images and to track blood vessels in angiograms.
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183. | Park, JS, and Han, JH, "Estimating optical flow by tracking contours," PATTERN RECOGNITION LETTERS, vol. 18, pp. 641-648, 1997.
Abstract:
We present a novel method of velocity field estimation for the points
on moving contours in a 2-D image sequence. The method determines the
corresponding point in a next image frame by minimizing the curvature
change of a given contour point. As a first step, snakes are used to
locate smooth curves in 2-D imagery. Thereafter, the extracted curves
are tracked continuously computing the corresponding point for each
contour point. (C) 1997 Published by Elsevier Science B.V.
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184. | Hozumi, T, Yoshida, K, Yoshioka, H, Yagi, T, Akasaka, T, Takagi, T, Nishiura, M, Watanabe, M, and Yoshikawa, J, "Echocardiographic estimation of left ventricular cavity area with a newly developed automated contour tracking method," JOURNAL OF THE AMERICAN SOCIETY OF ECHOCARDIOGRAPHY, vol. 10, pp. 822-829, 1997.
Abstract:
Development of an automated contour tracking method provides detection
and tracking of the endocardial boundary using the energy minimization
method without tracing a region of interest. The purpose of this study
was to compare the automated contour tracking method and manually drawn
methods for the measurement of left ventricular cavity areas and
fractional area change. Apical four-chamber view was visualized and
recorded for off-line analysis in 11 patients by means of
two-dimensional echocardiography. The automated contour tracking method
automatically traces the endocardial border from the recorded images
and calculates left ventricular cavity areas (end-diastole and
end-systole) and fractional area change. In the same images selected as
end-diastole and end-systole in the automated contour tracking method,
left ventricular endocardial border was manually traced to calculate
left ventricular cavity areas and fractional area change. Both methods
were compared by Linear regression analysis for the measurement of
cavity areas and fractional area change. Left ventricular areas
measured by the automated contour tracking method showed an excellent
correlation with those by the manual method (end-diastole: r = 0.99, y
= 0.83x + 2.6, standard error of the estimate = 1.5 cm(2); end-systole:
r = 0.99, y = 0.96x - 0.8, standard error of the estimate = 1.2 cm(2)).
The mean differences between the automated contour tracking and manual
methods were -3.1 +/- 5.1 cm(2) and -1.6 +/- 2.4 cm(2) at end-diastole
and end-systole, respectively. Fractional area change determined by the
automated contour tracking method correlated well with that by the
manual method (r = 0.95, y = 1.17x - 6.5, standard error of the
estimate = 3.4%). The mean difference between the automated contour
tracking and manual methods was -0.8% +/- 7.1%. In conclusion, a newly
developed automated contour tracking method correlates highly with the
manual method for the estimation of left ventricular cavity areas and
fractional area change in high-quality images. This suggests that this
new technique may be useful in the automated quantitation of left
ventricular function in patients with high-quality images with no
dropout and no intercavity artifact or structure.
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185. | Fasel, JHD, Gingins, P, Kalra, P, MagnenatThalmann, N, Baur, C, Cuttat, JF, Muster, M, and Gailloud, P, "Liver of the ''visible man''," CLINICAL ANATOMY, vol. 10, pp. 389-393, 1997.
Abstract:
Endoscopic surgery, also called minimally invasive surgery, is presumed
drastically to reduce postoperative morbidity and thus to offer both
human and economic benefits. For the surgeon, however, this approach
leads to a number of gestural challenges that require extensive
training to be mastered. In order to replace experimentation on animals
and patients, we developed a simulator for endoscopic surgery. To
achieve this goal, a first step was to develop a working prototype, a
''standard patient,'' on which the informatic and microengineering
tools could be validated. We used the visible man dataset for this
purpose. The external shape of the Visible man's liver, his biliary
passages, and his extrahepatic portal system turned out to be fully
within the standard pattern of normal anatomy. Anatomic Variations were
observed in the intrahepatic right portal vein, the hepatic veins, and
the arterial blood supply to the liver. Thus, the visible man dataset
reveals itself to be well suited for the simulation of minimally
invasive surgical operation such as endoscopic cholecystectomy. (C)
1997 Wiley-Liss, Inc.
|
186. | Breen, DE, "Cost minimization for animated geometric models in computer graphics," JOURNAL OF VISUALIZATION AND COMPUTER ANIMATION, vol. 8, pp. 201-220, 1997.
Abstract:
This paper describes how the concept of imposing geometric constraints
by minimizing cost functions may be used and extended to accomplish a
variety of animated modelling tasks for computer graphics. In this
approach a complex 3-D geometric problem is mapped into a scalar
minimization formulation. The mapping provides a straightforward method
for converting abstract geometric concepts into a construct that is
easily computed, The minimization approach is demonstrated in three
application areas: computer animation, visualization, and
physically-based modelling. In the computer animation application, cost
minimization may be used to generate motion paths and joint parameters
for animated actors. The approach may also be used to generate
deformable models that extract closed 3-D geometric models from volume
data for visualization, In the final application, the approach provides
the fundamental structure to a physically-based model of woven cloth.
(C) 1997 John Wiley & Sons, Ltd.
|
187. | Hanson, KM, Cunningham, GS, and McKee, RJ, "Uncertainty assessment for reconstructions based on deformable geometry," INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, vol. 8, pp. 506-512, 1997.
Abstract:
Deformable geometric models can be used in the context of Bayesian
analysis to solve ill-posed tomographic reconstruction problems. The
uncertainties associated with a Bayesian analysis may be assessed by
generating a set of random samples from the posterior, which may be
accomplished using a Markov Chain Monte Carlo (MCMC) technique. We
demonstrate the combination of these techniques for a reconstruction of
a two-dimensional object from two orthogonal noisy projections. The
reconstructed object is modeled in terms of a deformable geometrically
defined boundary with a uniform interior density yielding a nonlinear
reconstruction problem. We show how an MCMC sequence can be used to
estimate uncertainties in the location of the edge of the reconstructed
object. (C) 1997 John Wiley & Sons, Inc.
|
188. | Guy, G, and Medioni, G, "Inference of surfaces, 3D curves, and junctions from sparse, noisy, 3D data," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 1265-1277, 1997.
Abstract:
We address the problem of obtaining dense surface information from a
sparse set of 3D data in the presence of spurious noise samples. The
input can be in the form of points, or points with an associated
tangent or normal, allowing both position and direction to be corrupted
by noise. Most approaches treat the problem as an interpolation
problem, which is solved by fitting a surface such as a membrane or
thin plate to minimize some function. We argue that these physical
constraints are not sufficient, and propose to impose additional
perceptual constraints such as good continuity and ''cosurfacity.''
These constraints allow us to not only infer surfaces, but also to
detect surface orientation discontinuities, as well as junctions, all
at the same time. The approach Imposes no restriction on genus, number
of discontinuities, number of objects, and is noniterative. The result
is in the form of three dense saliency maps for surfaces, intersections
between surfaces (i.e., 3D curves), and 3D junctions, respectively.
These saliency maps are then used to guide a ''marching'' process to
generate a description (e.g., a triangulated mesh) making information
about surfaces, space curves, and 3D junctions explicit. The
traditional marching process needs to be refined as the polarity of the
surface orientation is not necessarily locally consistent. These three
maps are currently not integrated, and this is the topic of our ongoing
research. We present results on a variety of computer-generated and
real data, having varying curvature, of different genus, and multiple
objects.
|
189. | Sapiro, G, "Color snakes," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 68, pp. 247-253, 1997.
Abstract:
A framework for object segmentation in vector-valued images is
presented in this paper. The first scheme proposed is based on
geometric active contours moving toward the objects to be detected in
the vector-valued image. Object boundaries are obtained as geodesics or
minimal weighted-distance curves, where the metric is given by a
definition of edges in vector-valued data. The curve flow corresponding
to the proposed active contours holds formal existence, uniqueness,
stability, and correctness results. The scheme automatically handles
changes in the deforming curve topology. The technique is applicable,
for example, to color and texture images as well as multiscale
representations. We then present an extension of these vector active
contours, proposing a possible image flow for vector-valued image
segmentation. The algorithm is based on moving each one of the image
level sets according to the proposed vector active contours. This
extension also shows the relation between active contours and a number
of partial-differential-equations-based image processing algorithms as
anisotropic diffusion and shock filters. (C) 1997 Academic Press.
|
190. | Ip, HHS, and Wong, WH, "Detecting perceptually parallel curves: Criteria and force-driven optimization," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 68, pp. 190-208, 1997.
Abstract:
We have developed several theorems for the detection of parallel curves
in the continuous space. In this paper, we studied issues in carrying
the continuous algorithm to the discrete case and also the perceptual
characteristics leading to human recognition of parallelism. By
formulating these properties in terms of several distinctive forces, we
developed a force-driven model as a new optimization strategy to
perform correspondence establishment between points in the matching
curves. This force-driven mechanism provides a good coupling (or
correspondence matching) result, which is the prerequisite for the
correct detection of parallelism between curves. Convergence of the
algorithm and implementation efficiency are also investigated and
discussed. Experimental results on the relative weightings of these
forces also shed light on the perceptual priority imposed by the human
vision system. (C) 1997 Academic Press.
|
191. | Siddiqi, K, Kimia, BB, and Shu, CW, "Geometric shock-capturing ENO schemes for subpixel interpolation, computation and curve evolution," GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 59, pp. 278-301, 1997.
Abstract:
Subpixel methods that locate curves and their singularities, and that
accurately measure geometric quantities, such as orientation and
curvature, are of significant importance in computer vision and
graphics. Such methods often use local surface fits or structural
models for a local neighborhood of the curve to obtain the interpolated
curve. Whereas their performance is good in smooth regions of the
curve, it is typically poor in the vicinity of singularities.
Similarly, the computation of geometric quantities is often regularized
to deal with noise present in discrete data. However, in the process,
discontinuities are blurred over, leading to poor estimates at them and
in their vicinity. In this paper we propose a geometric interpolation
technique to overcome these limitations by locating curves and
obtaining geometric estimates while (1) not blurring across
discontinuities and (2) explicitly and accurately placing them, The
essential idea is to avoid the propagation of information across
singularities. This is accomplished by a one-sided smoothing technique,
where information is propagated from the direction of the side with the
''smoother'' neighborhood. When both sides are nonsmooth, the two
existing discontinuities are relieved by placing a single
discontinuity, or shock. The placement of shacks is guided by geometric
continuity constraints, resulting in subpixel interpolation with
accurate geometric estimates. Since the technique was originally
motivated by curve evolution applications, we demonstrate its
usefulness in capturing not only smooth evolving curves, but also ones
with orientation discontinuities. In particular, the technique is shown
to be far better than traditional methods when multiple or entire
curves are present in a very small neighborhood. (C) 1997 Academic
Press.
|
192. | Goudail, F, and Refregier, P, "Optimal target tracking on image sequences with a deterministic background," JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, vol. 14, pp. 3197-3207, 1997.
Abstract:
Until now, most optical pattern recognition filters have been designed
to process one image at a time. However, in image sequences, successive
frames are highly correlated, so that it is useful to take this
correlation into account while designing the filter. We develop a
target tracking processor following this method. The images are assumed
to consist of a moving object appearing against a moving background. A
model that takes into account two successive frames is designed. From
this model we determine the maximum-likelihood processor for tracking
the object from one frame to the next. Since this processor is based on
correlation operations, it could be implemented on a hybrid
optoelectronic system that makes use of the rapidity of optical
correlation. (C) 1997 Optical Society of America.
|
193. | Noll, D, and vonSeelen, W, "Object recognition by deterministic annealing," IMAGE AND VISION COMPUTING, vol. 15, pp. 855-860, 1997.
Abstract:
In this paper we describe a feature-based approach to object
recognition. The correspondence problem is solved by optimization of an
energy function. While similar approaches suffer from local minima, we
derive an energy function suitable for minimizing by deterministic
annealing. Hereby global optimization can be achieved. Algorithms
matching model features to image features in a coarse-to-fine manner
are described. (C) 1997 Elsevier Science B.V.
|
194. | Seitz, SM, and Dyer, CR, "View-invariant analysis of cyclic motion," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 25, pp. 231-251, 1997.
Abstract:
This paper presents a general framework for image-based analysis of 3D
repeating motions that addresses two limitations in the state of the
art. First, the assumption that a motion be perfectly even from one
cycle to the next is relaxed. Real repeating motions tend not to be
perfectly even, i.e., the length of a cycle varies through time because
of physically important changes in the scene. A generalization of
period is defined for repeating motions that makes this temporal
variation explicit. This representation, called the period trace, is
compact and purely temporal, describing the evolution of an object or
scene without reference to spatial quantities such as position or
velocity. Second, the requirement that the observer be stationary is
removed. Observer motion complicates image analysis because an object
that undergoes a 3D repeating motion will generally not produce a
repeating sequence of images. Using principles of affine invariance, we
derive necessary and sufficient conditions for an image sequence to be
the projection of a 3D repeating motion, accounting for changes in
viewpoint and other camera parameters. Unlike previous work in visual
invariance, however, our approach is applicable to objects and scenes
whose motion is highly non-rigid. Experiments on real image sequences
demonstrate how the approach may be used to detect several types of
purely temporal motion features, relating to motion trends and
irregularities. Applications to athletic and medical motion analysis
are discussed.
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195. | Neuenschwander, WM, Fua, P, Iverson, L, Szekely, G, and Kubler, O, "Ziplock snakes," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 25, pp. 191-201, 1997.
Abstract:
We propose a snake-based approach that allows a user to specify only
the distant end points of the curve he wishes to delineate without
having to supply an almost complete polygonal approximation. This
greatly simplifies the initialization process and yields excellent
convergence properties. This is achieved by using the image information
around the end points to provide boundary conditions and by introducing
an optimization schedule that allows a snake to take image information
into account first only near its extremities and then, progressively,
toward its center. In effect, the snakes are clamped onto the image
contour in a manner reminiscent of a ziplock being closed.
These snakes can be used to alleviate the often repetitive task
practitioners face when segmenting images by eliminating the need to
sketch a feature of interest in its entirety, that is, to perform a
painstaking, almost complete, manual segmentation.
|
196. | Dryden, IL, Mardia, KV, and Walder, AN, "Review of the use of context in statistical image analysis," JOURNAL OF APPLIED STATISTICS, vol. 24, pp. 513-538, 1997.
Abstract:
This paper is a review of the use of contextual information in
statistical image analysis. After defining what we mean by 'context',
we describe the Bayesian approach to high-level image analysis using
deformable templates. We describe important aspects of work on
character recognition and syntactic pattern recognition; in particular,
aspects of the work which are relevant to scene understanding. We
conclude with a review of some work on knowledge-based systems which
use context to aid object recognition.
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197. | Kervrann, C, Davoine, F, Perez, P, Forchheimer, R, and Labit, C, "Generalized likelihood ratio-based face detection and extraction of mouth features," PATTERN RECOGNITION LETTERS, vol. 18, pp. 899-912, 1997.
Abstract:
We describe a system to detect the speaker's face and mouth in
videophone sequences. A statistical scheme based on a subspace method
is described for detecting and tracking faces under varying poses. A
matching criterion based on a Generalized Likelihood Ratio is optimized
efficiently with respect to a perspective transformation using a
coarse-to-fine search strategy combined with a simulated annealing
algorithm. Moreover, we analyze the amplitude projections around the
speaker's mouth to describe the shape of the lips. All computations are
performed on lossy H263-coded images, The proposed algorithms are
well-suited to a further real-time implementation. (C) 1997 Elsevier
Science B.V.
|
198. | Proesmans, M, and Van Gool, L, "One-shot 3D-shape and texture acquisition of facial data," AUDIO- AND VIDEO-BASED BIOMETRIC PERSON AUTHENTICATION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1206, pp. 411-418, 1997.
Abstract:
In this paper we present new methods to simultaneously extract and
exploit the three-dimensional shape of a face and its surface texture.
It is based on an active technique, i.e. special illumination, but in
contrast to traditional active sensing does not require scanning or
sequential projection of multiple patterns. This one-shot nature of the
devise allows to capture moving objects, e.g. for making a 3D
reconstruction of a face even when the person is talking. The use of
the system is illustrated using simple methods to extract both textural
and geometrical features from faces, that can be used for
authentication purposes. The advantage of using 3D data is that both
types of features can be made more invariant under changes in head pose
or illumination conditions.
|
199. | Guttman, MA, Zerhouni, EA, and McVeigh, ER, "Analysis of cardiac function from MR images," IEEE COMPUTER GRAPHICS AND APPLICATIONS, vol. 17, pp. 30-38, 1997.
Abstract:
This paper describes an image metamorphosis technique to handle
scattered feature constraints specified with points, polylines, and
splines. Solutions to the following three problems are presented:
feature specification, warp generation, and transition control. We
demonstrate the use of snakes to reduce the burden of feature
specification. Next, we propose the use of multilevel free-form
deformations (MFFD) to compute C-2-continuous and one-to-one mapping
functions among the specified features. The resulting technique, based
on B-spline approximation, is simpler and faster than previous warp
generation methods. Furthermore, it produces smooth image
transformations without undesirable ripples and foldovers. Finally, we
simplify the MFFD algorithm to derive transition functions to control
geometry and color blending. Implementation details are furnished and
comparisons among Various metamorphosis techniques are presented.
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200. | Zhao, WY, Nandhakumar, N, and Smith, PW, "Model-based interpretation of stereo imagery of textured surfaces," MACHINE VISION AND APPLICATIONS, vol. 10, pp. 201-213, 1997.
Abstract:
We present a scheme for reliable and accurate surface reconstruction
from stereoscopic images containing only fine texture and no stable
high-level features. Partial shape information is used to improve
surface computation: first by fitting an approximate, global,
parametric model, and then by refining this model via local
correspondence processes. This scheme eliminates the window size
selection problem in existing area-based stereo correspondence schemes,
These ideas are integrated in a practical vision system that is being
used by environmental scientists to study wind erosion of bulk material
such as coal ore being transported in open rail cars.
|
201. | Hinshaw, KP, and Brinkley, JF, "Using 3-D shape models to guide segmentation of MR brain images," JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, vol. 10, pp. 469-473, 1997.
Abstract:
Accurate segmentation of medical images poses one of the major
challenges in computer vision. Approaches that rely solely on intensity
information frequently fail because similar intensity values appear in
multiple structures. This paper presents a method for using shape
knowledge to guide the segmentation process, applying it to the task of
finding the surface of the brain. A 3-D model that includes local shape
constraints is fitted to an MR volume dataset. The resulting
low-resolution surface is used to mask out regions far from the
cortical surface, enabling an isosurface extraction algorithm to
isolate a more detailed surface boundary. The surfaces generated by
this technique are comparable to those achieved by other methods,
without requiring user adjustment of a large number of ad hoc
parameters.
|
202. | Le Goualher, G, Barillot, C, and Bizais, Y, "Modeling cortical sulci with active ribbons," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 11, pp. 1295-1315, 1997.
Abstract:
We propose a method for the 3D segmentation and representation of
cortical folds with a special emphasis on the cortical sulci. These
cortical structures are represented using "active ribbons". Active
ribbons are built from active surfaces, which represent the median
surface of a particular sulcus filled by CSF. Sulci modeling is
obtained from MRI acquisitions (usually T1 images). The segmentation is
performed using an automatic labeling procedure to separate gyri from
sulci based on curvature analysis of the different iso-intensity
surfaces of the original MRI volume. The outer parts of the sulci are
used to initialize the convergence of the active ribbon from the outer
parts of the brain to the interior. This procedure has two advantages:
first, it permits the labeling of voxels belonging to sulci on the
external part of the brain as well as on the inside (which is often the
hardest point) and secondly, this segmentation allows 3D visualization
of the sulci in the MRI volumetric environment as well as showing the
sophisticated shapes of the cortical structures by means of isolated
surfaces. Active ribbons can be used to study the complicated shape of
the cortical anatomy, to model the variability of these structures in
shape and position, to assist nonlinear registrations of human brains
by locally controlling the warping procedure, to map brain
neurophysiological functions into morphology or even to select the
trajectory of an intra-sulci (virtual) endoscope.
|
203. | Marescaux, J, Clement, JM, Nord, M, Russier, Y, Tassetti, V, Mutter, D, Cotin, S, and Ayache, N, "A new concept in digestive surgery: the computer assisted surgical procedure, from virtual reality to telemanipulation," BULLETIN DE L ACADEMIE NATIONALE DE MEDECINE, vol. 181, pp. 1609-1623, 1997.
Abstract:
Surgical simulation increasingly appears to be an essential aspect of
tomorrow's surgery The development of a hepatic surgery simulator is an
advanced concept calling for a new writing system which will transform
the medical world. virtual reality: Virtual reality extends the
perception of our five senses by representing more than rite real state
of things by the means of computer sciences and robotics. It consists
of three concepts : immersion, navigation and interaction. Three
reasons have led tts to develop this simulator: the first:rt is to
provide the surgeon with a comprehensive visualisation of the organ.
The second reason is to allow for planning and surgical simulation that
could be compared with the detailed flight-plan for a commercial jet
pilot. The third lies in the fact that virtual reality is an integrated
part of the concept of computer assisted surgical procedure. The
project consists of a sophisticated simulator which has to include five
requirements, : visual fidelity: interactivity: physical properties,
physiological properties, sensory input and output. In this report we
will describe how to get a realistic 3D model of the liver from
bi-dimensional 2D medical images for anatomical and surgical training.
The introduction of a tumor and the consequent planning and virtual
resection is also described as are force feedback and real-time
interaction.
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204. | Held, K, Kops, ER, Krause, BJ, Wells, WM, Kikinis, R, and Muller-Gartner, HW, "Markov random field segmentation of brain MR images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 878-886, 1997.
Abstract:
We describe a fully automatic three-dimensional (3-D)-segmentation
technique for brain magnetic resonance (MR) images, By means of Markov
random fields (MRF's) the segmentation algorithm captures three
features that are of special importance for MR images, i.e.,
nonparametric distributions of tissue intensities, neighborhood
correlations, and signal inhomogeneities, Detailed simulations and real
MR images demonstrate the performance of the segmentation algorithm, In
particular, the impact of noise, inhomogeneity, smoothing, and
structure thickness are analyzed quantitatively, Even single-echo MR
images are well classified into gray matter, white matter,
cerebrospinal fluid, scalp-bone, and background, A simulated annealing
and an iterated conditional modes implementation are presented.
|
205. | Gilson, SJ, and Damper, RI, "An empirical comparison of neural techniques for edge linking of images," NEURAL COMPUTING & APPLICATIONS, vol. 6, pp. 64-78, 1997.
Abstract:
Edge linking is a fundamental computer vision task, yet presents
difficulties arising from the lack of information in the image. Viewed
ns a constrained optimisation problem, it is NP hard - being isomorphic
to the classical travelling salesman problem. Self-learning neural
techniques boast the ability to solve hard, ill-defined problems, and
hence offer promise for such an application, This paper examines the
suitability of four well-known unsupervised techniques for rite task of
edge linking, by applying them to a test bed of edge point images and
then evaluating their performance both quantitatively and
qualitatively. Techniques studied are the elastic net, active contours,
Kohonen map and Burr's modified elastic net. Of these, only the elastic
ner and the Kohonen map are realistic contenders for general
edge-linking tasks. However, the other two exhibit behaviour which may
make them particularly suited to some specific image-processing and
computer vision applications.
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206. | Delibasis, K, Undrill, PE, and Cameron, GG, "Designing texture filters with genetic algorithms: An application to medical images," SIGNAL PROCESSING, vol. 57, pp. 19-33, 1997.
Abstract:
The problem of texture recognition is addressed by studying appropriate
descriptors in the spatial frequency domain. During a training phase a
filter is configured to determine different classes of texture by the
response of its correlation with the Fourier spectrum of training-image
templates. This is achieved by genetic algorithm-based optimisation.
The technique is tested on standard texture patterns and then applied
to magnetic resonance images of the brain to segment the cerebellum
from the surrounding white and grey matter. Comparisons with
established texture recognition techniques are presented, which show
that the proposed method performs as well as, or better than,
traditional techniques for the chosen instances of standard and
anatomical texture and has the advantage of not having to decide which
texture measure to use for a specific image structure. (C) 1997
Elsevier Science B.V.
|
207. | Matsuyama, T, and Wada, T, "Cooperative spatial reasoning for image understanding," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 11, pp. 205-227, 1997.
Abstract:
Spatial Reasoning, reasoning about spatial information (i.e. shape end
spatial relations), is a crucial function of image understanding and
computer vision systems. This paper proposes a novel spatial reasoning
scheme for image understanding and demonstrates its utility and
effectiveness in two different systems: region segmentation and aerial
image understanding systems. The scheme is designed based on a
so-called Multi-Agent/Cooperative Distributed Problem Solving Paradigm,
where a group of intelligent agents cooperate with each other to
fulfill a complicated task. The first part of the paper describes a
cooperative distributed region segmentation system, where each region
in an image is regarded as an agent. Starting from seed regions given
at the initial stage, region agents deform their shapes dynamically so
that the image is partitioned into mutually disjoint regions. The
deformation of each individual region agent is realized by the snake
algorithm(14) and neighboring region agents cooperate with each other
to find common region boundaries between them. In the latter part of
the paper, we first give a brief description of the cooperative spatial
reasoning method used in our aerial image understanding system SIGMA.
In SIGMA, each recognized object such as a house and a road is regarded
as an agent. Each agent generates hypotheses about its neighboring
objects to establish spatial relations and to detect missing objects.
Then, we compare its reasoning method with that used in the region
segmentation system. We conclude the paper by showing further utilities
of the Multi-Agent/Cooperative Distributed Problem Solving Paradigm for
image understanding.
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208. | Dickinson, SJ, and Metaxas, D, "Using aspect graphs to control the recovery and tracking of deformable models," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 11, pp. 115-141, 1997.
Abstract:
Active or deformable models have emerged as a popular modelling
paradigm in computer vision. These models have the flexibility to adapt
themselves to the image data, offering the potential for both generic
object recognition and non-rigid object tracking. Because these active
models are underconstrained, however, deformable shape recovery often
requires manual segmentation or good model initialization, while active
contour trackers have been able to track only an object's translation
in the image. In this paper, we report our current progress in using a
part-based aspect graph representation of an object(14) to provide the
missing constraints on data-driven deformable model recovery and
tracking processes.
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209. | Delibasis, K, Undrill, PE, and Cameron, GG, "Designing Fourier descriptor-based geometric models for object interpretation in medical images using genetic algorithms," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 66, pp. 286-300, 1997.
Abstract:
In previous work we have modeled simple 3D anatomical objects using
deformed superquadrics and established their optimal position with the
aid of genetic algorithms (GAs). Here we extend the complexity of the
search object using 3D Fourier descriptor (FD) representations and
allow GAs once again to optimize the object's shape and position. Using
magnetic resonance image data, we perform an approximate segmentation
on one lateral ventricle in the brain and use the FDs from this as
seeding values for the GAs to search for the left and right lateral
ventricles in seven 3D data sets. We show that the method is capable of
coping with normal biological variation. Finally, we compare
FD/GA-guided segmentation with a manually guided interactive region
growing method and find an agreement of 78 +/- 10% in voxel
classification with a corresponding average edge placement error of 2.2
+/- 0.4 mm. (C) 1997 Academic Press.
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210. | Zhong, Y, and Jain, AK, "Object localization using color, texture and shape," ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1223, pp. 279-294, 1997.
Abstract:
We address the problem of localizing objects using color, texture and
shape. Given a handrawn sketch for querying an object shape, and its
color and texture, the algorithm automatically searches the database
images for objects which meet the query attributes. The database images
do not need to be presegmented or annotated. The proposed algorithm
operates in two stages. In the first stage, we use local texture and
color features to find a small number of candidate images, and identify
regions in the candidate images which share similar texture and color
as the query example. To speed up the processing, the texture and color
features are directly extracted from the Discrete Cosine Transform
(DCT) compressed domain. In the second stage, we use a deformable
template matching method to match the query shape to the image edges at
the locations which possess the desired texture and color attributes.
This algorithm is different from the other content-based image
retrieval algorithms in that: (i) no presegmentation of the database
images is needed, and (ii) the color and texture features are directly
extracted from the compressed images. Experimental results show that
substantial computational savings can be achieved utilizing multiple
image cues.
|
211. | Fua, P, "Consistent modeling of terrain and drainage using deformable models," ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1223, pp. 459-474, 1997.
Abstract:
We propose an automated approach to modeling drainage channels-and,
more generally, linear features that lie on the terrain-from multiple
images, which results not only in high-resolution, accurate and
consistent models of the features, but also of the surrounding terrain.
In our specific case, we have chosen to exploit the fact that rivers
flow downhill and lie at the bottom of local depressions in the
terrain, valley floors tend to be "U" shaped, and the drainage pattern
appears as a network of linear features that can be visually detected
in single gray-level images.
Different approaches have explored individual facets of this problem.
Ours unifies these elements in a common framework. We accurately model
terrain and features as 3-dimensional objects from several information
sources that may be in error and inconsistent with one another. This
approach allows us to generate models that are faithful to sensor data,
internally consistent and consistent with physical constraints. We have
proposed generic models that have been applied to the specific task at
hand-river delineation and data elevation model (DEM) refinement-and
show that the constraints can be expressed in a computationally
effective way and, therefore, enforced while initializing the models
and then fitting them to the data. We will also argue that the same
techniques are robust enough to work on other features that are
constrained by predictable forces.
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212. | Glasbey, CA, "SAR image registration and segmentation using an estimated DEM," ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1223, pp. 507-520, 1997.
Abstract:
Synthetic aperture radar (SAR) images are notoriously difficult to
interpret. Segmentation is simplified if a digital map is available, to
which the image can be registered. Also, registration is simplified if
a digital elevation model (DEM) is available. In this paper it is shown
that, if a DEM is unavailable, it can be estimated by minimising an
energy functional consisting of a measure of agreement between the SAR
image and a digital map together with a thin-plate bending-energy term.
A computationally-efficient, finite-element algorithm is proposed to
solve the optimisation problem. The method is applied to automatically
align an airborne SAR image with a digital map of field boundaries,
producing an image which is simultaneously registered and segmented.
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213. | Luettin, J, and Thacker, NA, "Speechreading using probabilistic models," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 65, pp. 163-178, 1997.
Abstract:
We describe a robust method for locating and tracking lips in
gray-level image sequences. Our approach learns patterns of shape
variability from a training set which constrains the model during image
search to only deform in ways similar to the training examples, Image
search is guided by a learned gray-level model which is used to
describe the large appearance variability of lips, Such variability
might be due to different individuals, illumination, mouth opening,
specularity, or visibility of teeth and tongue, Visual speech features
are recovered from the tracking results and represent both shape and
intensity information, We describe a speechreading (lip-reading)
system, where the extracted features are modeled by Gaussian
distributions and their temporal dependencies by hidden Markov models.
Experimental results are presented for locating lips, tracking lips,
and speechreading. The database used consists of a broad variety of
speakers and was recorded in a natural environment with no special
lighting or lip markers used, For a speaker independent digit
recognition task using visual information only, the system achieved an
accuracy about equivalent to that of untrained humans. (C) 1997
Academic Press.
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214. | Fua, P, and Brechbuhler, C, "Imposing hard constraints on deformable models through optimization in orthogonal subspaces," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 65, pp. 148-162, 1997.
Abstract:
An approach is presented for imposing generic hard constraints an
deformable models at a low computational cost, while preserving the
good convergence properties of snake-like models. We believe this
capability to be essential not only for the accurate modeling of
individual objects that obey known geometric and semantic constraints
but also for the consistent modeling of sets of objects. Many of the
approaches to this problem that have appeared in the vision literature
rely on adding penalty terms to the objective functions. They rapidly
become intractable when the number of constraints increases, Applied
mathematicians have developed powerful constrainted optimization
algorithms that, in theory, can address this problem. However, these
algorithms typically do not take advantage of the specific properties
of snakes, We have therefore designed a new algorithm that is closely
related to Lagrangian methods but is tailored to accommodate the
particular brand of deformable models used in the image understanding
community, We demonstrate the validity of our approach first in two
dimensions using synthetic images and then in three dimensions using
real aerial images to simultaneously model terrain, roads, and
ridgelines under consistency constraints. (C) 1997 Academic Press.
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215. | Undrill, PE, Delibasis, K, and Cameron, GG, "An application of genetic algorithms to geometric model-guided interpretation of brain anatomy," PATTERN RECOGNITION, vol. 30, pp. 217-227, 1997.
Abstract:
This work applies 3D Fourier Descriptors (FDs) and Genetic Algorithms
(GAs) to the optimisation of the shape and position of models of
anatomical objects within the human brain. Using magnetic resonance
image data, we perform an approximate segmentation on one lateral
ventricle and use the FDs from this as seeding values for the GAs to
search for the left and right lateral ventricles in subsequent 3D image
data sets, showing that the method is capable of coping with normal
biological variation within and between individuals. Finally, we
compare the GA-guided segmentation with a manual region growing method
and find an agreement of 79.9+/-5.8% in voxel classification with a
corresponding mean edge placement error of 2.1+/-0.4 mm. Copyright (C)
1997 Pattern Recognition Society.
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216. | Jain, AK, and Dorai, C, "Practicing vision: Integration, evaluation and applications," PATTERN RECOGNITION, vol. 30, pp. 183-196, 1997.
Abstract:
Computer vision has emerged as a challenging and important area of
research, both as an engineering and a scientific discipline. The
growing importance of computer vision is evident from the fact that it
was identified as one of the ''Grand Challenges'' and also from its
prominent role in the National Information Infrastructure. While the
design of a general purpose vision system continues to be elusive,
machine vision systems are being used successfully in specific
application domains. Building a practical vision system requires a
careful selection of appropriate sensors, extraction and integration of
information from available cues in the sensed data, and evaluation of
system robustness and performance. We discuss and demonstrate
advantages of (i) multi-sensor fusion, (ii) combination of features and
classifiers, (iii) integration of visual modules, and (iv)
admissibility and goal-directed evaluation of vision algorithms. The
requirements of several prominent real world applications such as
biometry, document image analysis, image and video database retrieval,
and automatic object model construction offer exciting problems and new
opportunities to design and evaluate vision algorithms. Copyright (C)
1997 Pattern Recognition Society.
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217. | Yezzi, A, Kichenassamy, S, Kumar, A, Olver, P, and Tannenbaum, A, "A geometric snake model for segmentation of medical imagery," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 199-209, 1997.
Abstract:
In this note, we employ the new geometric active contour models
formulated in [25] and [26] for edge detection and segmentation of
magnetic resonance imaging (MRI), computed tomography (CT), and
ultrasound medical imagery, Our method is based on defining
feature-based metrics on a given image which in turn leads to a novel
snake paradigm in which the feature of interest mag be considered to
lie at the bottom of a potential well, Thus, the snake is attracted
very quickly and efficiently to the desired feature.
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218. | Caselles, V, Kimmel, R, and Sapiro, G, "Geodesic active contours," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 22, pp. 61-79, 1997.
Abstract:
A novel scheme for the detection of object boundaries is presented. The
technique is based on active contours evolving in time according to
intrinsic geometric measures of the image. The evolving contours
naturally split and merge, allowing the simultaneous detection of
several objects and both interior and exterior boundaries. The proposed
approach is based on the relation between active contours and the
computation of geodesics or minimal distance curves. The minimal
distance curve lays in a Riemannian space whose metric is defined by
the image content. This geodesic approach for object segmentation
allows to connect classical ''snakes'' based on energy minimization and
geometric active contours based on the theory of curve evolution.
Previous models of geometric active contours are improved, allowing
stable boundary detection when their gradients suffer from large
variations, including gaps. Formal results concerning existence,
uniqueness, stability, and correctness of the evolution are presented
as well. The scheme was implemented using an efficient algorithm for
curve evolution. Experimental results of applying the scheme to real
images including objects with holes and medical data imagery
demonstrate its power. The results may be extended to 3D object
segmentation as well.
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219. | Dachman, AH, Lieberman, J, Osnis, RB, Chen, SYJ, Hoffmann, KR, Chen, CT, Newmark, GM, and McGill, J, "Small simulated polyps in pig colon: Sensitivity of CT virtual colography," RADIOLOGY, vol. 203, pp. 427-430, 1997.
Abstract:
PURPOSE: The authors evaluated computed tomographic (CT) virtual
colography for the detection of simulated polyps under ideal
conditions, as well as the effects on lesion conspicuity of (a)
collimation, (b) table pitch, and (c) orientation of the colon lumen
with respect to the gantry.
MATERIALS AND METHODS: Pig colon was resected and cleansed, and polyps
with diameters of 3, 7, and 10 mm were created. Each specimen was
scanned with collimation of 5 and 7 mm and table pitch of 1.0, 1.6, and
2.0 at angles of 0 degrees, 45 degrees, and 90 degrees to the gantry.
The initial two-dimensional (2D) images were reconstructed at 1-mm
intervals (2D reconstructions), from which three-dimensional (3D)
virtual colography images were generated. Polyp conspicuity on the
initial and reconstructed 2D images and the 3D reconstructions was
evaluated on a three-point scale: 0 = polyp not depicted, 1 = polyp
faintly depicted, and 2 = polyp clearly depicted.
RESULTS: The 10-mm-diameter polyp was clearly depicted (grade 2
conspicuity) on every initial and reconstructed 2D image and 3D
reconstruction without regard to collimation, table pitch, or angle to
the gantry. The 7-mm-diameter polyp was clearly depicted (grade 2
conspicuity) on every initial and reconstructed 2D image, but
conspicuity on 3D reconstructions varied as the imaging parameters
varied. The 3-mm-diameter polyp was faintly depicted (grade 1
conspicuity) on the initial and reconstructed 2D images and 3D
reconstructions, but conspicuity varied on the 3D reconstructions as
the imaging parameters varied.
CONCLUSION: CT virtual colography helped detection of small mucosal
polyps regardless of the angle of the colon lumen to the gantry at
which they were obtained.
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220. | Friedland, NS, and Rosenfeld, A, "An integrated approach to 2D object recognition," PATTERN RECOGNITION, vol. 30, pp. 525-535, 1997.
Abstract:
A multilevel Markov Random Field (MRF) energy environment has been
developed that simultaneously performs delineation, representation and
classification of two-dimensional objects by using a global
optimization technique. This environment supports a multipolar shape
representation which establishes a dynamic MRF structure. This
structure is initialized as a single-center polar representation, and
uses minimum description length tests to determine whether to establish
new polar centers. The polar representations at these centers are
compared with a database of such representations in order to identify
pieces of objects, and the results of these comparisons are used to
compile evidence for global object identifications. This method is
potentially more robust than conventional multistaged approaches to
object recognition because it incorporates all the information about
the objects into a single adaptive decision process, and its use of a
multipolar representation allows it to handle partially occluded
objects.
|
221. | Deng, JY, and Lai, FP, "Region-based template deformation and masking for eye-feature extraction and description," PATTERN RECOGNITION, vol. 30, pp. 403-419, 1997.
Abstract:
We propose an improved method for eye-feature extraction, descriptions,
and tracking using deformable templates. Some existing algorithms are
exploited to locate the initial position of eye features and then
deformable templates are used for extracting and describing the eye
features. Rather than using original energy minimization for matching
the templates, the region-based approach is proposed for template
deformation. Based on the region properties, the new strategy avoids
problems such as template shrinking, adjusting the weights of energy
terms, failure of orientation adjustment due to some exceptional cases.
Our strategies are also coupled with Canny edge operator to give a new
back-end processing. By integrating the local edge information from the
edge detection and the global collector from our region-based template
deformation, this processing stage can generate accurate eye-feature
descriptions. Finally, the template deformation process is applied to
tracking eye features. (C) 1997 Pattern Recognition Society.
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222. | Katkere, A, Moezzi, S, Kuramura, DY, Kelly, P, and Jain, R, "Towards video-based immersive environments," MULTIMEDIA SYSTEMS, vol. 5, pp. 69-85, 1997.
Abstract:
Video provides a comprehensive visual record of environment activity
over time. Thus, video data is an attractive source of information for
the creation of virtual worlds which require some real-world fidelity.
This paper describes the use of multiple streams of video data for the
creation of immersive virtual environments. We outline our multiple
perspective interactive video (MPI-Video) architecture which provides
the infrastructure for the processing and analysis of multiple streams
of video data. Our MPI-Video system performs automated analysis of the
raw video and constructs a model of the environment and object activity
within this environment. This model provides a comprehensive
representation of the world monitored by the cameras which, in turn,
can be used in the construction of a virtual world. In addition, using
the information produced and maintained by the MPI-Video system; our
immersive video system generates virtual video sequences. These are
sequences of the dynamic environment from an arbitrary view point
generated using the real camera data. Such sequences allow a user to
navigate through the environment and provide a sense of immersion in
the scene. We discuss results from our MPI-Video prototype, outline
algorithms for the construction of virtual views and provide examples
of a variety of such immersive video sequences.
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223. | Bloomgarden, DC, Fayad, ZA, Ferrari, VA, Chin, B, Sutton, MGSJ, and Axel, L, "Global cardiac function using fast breath-hold MRI: Validation of new acquisition and analysis techniques," MAGNETIC RESONANCE IN MEDICINE, vol. 37, pp. 683-692, 1997.
Abstract:
Calculation of global cardiac function parameters has been validated
using fast, segmented k-space, breath-hold, gradient-echo, magnetic
resonance images. Images of phantoms, experimental animals, normal
volunteers, and patients were acquired with a 1.5 T clinical scanner,
Humans were imaged using two phased-array surface coils in multicoil
mode, Myocardial contours were extracted using a new interactive,
semi-automated method based on the active contour model method, Images
were acquired in the short-axis orientation, and, using a new imaging
and analysis strategy, in rotating plane long-axis orientations, to
provide better definition of the valve planes and the apex, and also to
reduce the number of slices (compared with the short-axis method)
required to sample the whole heart, Validation was accomplished through
calculation of the volumes of phantoms and left and right ventricular
masses of animal hearts. Functional parameters from MRI were compared
with those from echocardiograms and radionuclide angiograms in normal
volunteers and patients, respectively.
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224. | Refregier, P, Germain, O, and Gaidon, T, "Optimal snake segmentation of target and background with independent Gamma density probabilities, application to speckled and preprocessed images," OPTICS COMMUNICATIONS, vol. 137, pp. 382-388, 1997.
Abstract:
We propose in this paper a snake-based segmentation processor to track
the shape of a target with random white intensity appearing on a random
white spatially disjoint background. We study the optimal solution for
Gamma laws and we discuss the relevance of such statistics for
realistic situations. This algorithm, based on an active contour model
(snakes), consists in correlations of a binary reference with the scene
image or with pre-processed version of the scene image. This method is
a generalization of correlation techniques and thus opens new
applications for digital and optical correlators.
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225. | Caselles, V, Kimmel, R, and Sapiro, G, "Minimal surfaces based object segmentation," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 394-398, 1997.
Abstract:
A geometric approach for 3D object segmentation and representation is
presented. The segmentation is obtained by deformable surfaces moving
towards the objects to be detected in the 3D image. The model is based
on curvature motion and the computation of surfaces with minimal areas,
better known as minimal surfaces. The space where the surfaces are
computed is induced from the 3D image (volumetric data) in which the
objects are to be detected. The model links between classical
deformable surfaces obtained via energy minimization, and intrinsic
ones derived from curvature based flows. The new approach is stable,
robust, and automatically handles changes in the surface topology
during the deformation.
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226. | Delp, SL, Loan, P, Basdogan, C, and Rosen, JM, "Surgical simulation: An emerging technology for training in emergency medicine," PRESENCE-TELEOPERATORS AND VIRTUAL ENVIRONMENTS, vol. 6, pp. 147-159, 1997.
Abstract:
The current methods of training medical personnel to provide emergency
medical care have several important shortcomings. For example, in the
training of wound debridement techniques, animal models are used to
gain experience treating traumatic injuries. We propose an alternative
approach by creating a three-dimensional, interactive computer model of
the human body that can be used within a virtual environment to learn
and practice wound debridement techniques and Advanced Trauma Life
Support (ATLS) procedures. As a first step, we have developed a
computer model that represents the anatomy and physiology of a normal
and injured lower limb. When visualized and manipulated in a virtual
environment, this computer model will reduce the need for animals in
the training oi-trauma management and potentially provide a superior
training experience. This article describes the development choices
that were made in implementing the preliminary system and the
challenges that must be met to create an effective medical training
environment.
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227. | Sclaroff, S, "Deformable prototypes for encoding shape categories in image databases," PATTERN RECOGNITION, vol. 30, pp. 627-641, 1997.
Abstract:
An image database search method is described that uses strain energy
from prototypes to represent shape categories. Rather than directly
comparing a candidate shape with all entries in a database, shapes are
ordered in terms of non-rigid deformations that relate them to a small
subset of representative prototypes. Shape correspondences are obtained
via modal matching, a decomposition for matching, describing, and
comparing shapes despite sensor variations and non-rigid deformations.
Deformation is decomposed into an ordered basis of orthogonal principal
components. This allows selective invariance to in-plane rotation,
translation, and scaling, and quasi-invariance to affine deformations.
Retrieval accuracy and stability are evaluated in experiments with 2-D
image databases. (C) 1997 Pattern Recognition Society.
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228. | Fejes, S, and Rosenfeld, A, "Discrete active models and applications," PATTERN RECOGNITION, vol. 30, pp. 817-835, 1997.
Abstract:
Optimization processes based on ''active models'' play central roles in
many areas of computational vision as well as computational geometry.
Unfortunately, current models usually require highly complex and
sophisticated mathematical machinery and at the same time they suffer
from a number of limitations which impose restrictions on their
applicability. In this paper a simple class of discrete active models,
called migration processes (MPs), is presented. The processes are based
on iterated averaging over neighborhoods defined by constant geodesic
distance. It is demonstrated that the MP model-a system of
self-organizing active particles-has a number of advantages over
previous models, both parametric active models (''snakes'') and
implicit (contour evolution) models. Due to the generality of the MP
model, the process can be applied to derive natural solutions to a
variety of optimization problems,including defining (minimal) surface
patches given their boundary curves; finding shortest paths joining
sets of points; and decomposing objects into ''primitive'' parts. (C)
1997 Pattern Recognition Society.
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229. | Liang, KH, Tjahjadi, T, and Yang, YH, "Roof edge detection using regularized cubic B-spline fitting," PATTERN RECOGNITION, vol. 30, pp. 719-728, 1997.
Abstract:
A scheme employing one-dimensional (1-D) Regularized Cubic B-Spline
(RCBS) fitting [G. Chen and Y. H. Yang, IEEE Trans. Systems Man
Cybernet. 25, 636-693 (1995)] has been used successfully in the task of
step edge detection. The regularized fitting is transformed into a
quadratic energy equation to simplify the computation. This scheme,
however, has three major limitations: it is non-linear, has a limited
accuracy and is computationally expensive. This paper presents a
modified scheme which overcomes these limitations. The modified scheme
employs the I-D RCBS fitting on the horizontal and Vertical
orientations of a window of an image to generate two I-D signals, which
provide sufficient information about the local property of the
sub-image for roof edge detection. Experimental results show that the
scheme of roof edge detection is very sensitive to small signals. (C)
1997 Pattern Recognition Society.
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230. | Chin, TM, and Mariano, AJ, "Space-time interpolation of oceanic fronts," IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 35, pp. 734-746, 1997.
Abstract:
Oceanic temperature fronts observed through composite infrared images
from the AVHRR satellite data are fragmented due mostly to cloud
occlusion. The sampling frequency of such frontal position observations
tends to be insufficiently high to resolve dynamics of the meandering
features associated with the frontal contour, so that contour
reconstruction using a standard space-time smoothing often leads to
introduction of spurious features. Augmenting space-time smoothing with
a simple point-feature detection/matching scheme, however, can
dramatically improve the reconstruction product, This paper presents
such a motion-compensated interpolation algorithm, for reconstruction
of open contours evolving in time given fragmented position data, The
reconstruction task is formulated as an optimization problem, and a
time-sequential solution which adaptively estimates feature motion is
provided. The resulting algorithm reliably interpolates position
measurements of the surface temperature fronts associated with the
highly convoluted portions of strong ocean currents such as the Gulf
Stream and Kuroshio.
|
231. | Sebbahi, A, Herment, A, deCesare, A, and Mousseaux, E, "Multimodality cardiovascular image segmentation using a deformable contour model," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 21, pp. 79-89, 1997.
Abstract:
An automatic segmentation method has been developed for cardiovascular
multimodality imaging. A ''snake'' model based on a curve shaping and
an energy-minimizing process is used to detect blood-wall interfaces on
Cine-CT, MRI and ultrasound images. Deformation of a reduced set of
contour points was made according to a discretized global, regional and
local minimum energy criterion. A continuous regional optimization
process was also integrated into the deformation model, it takes into
account a cubic spline interpolation and adaptive regularity
constraints. The constraints provided rapid convergence toward a final
contour position by successively stopping spline segments. (C) 1997
Elsevier Science Ltd.
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232. | Olabarriaga, SD, and Smeulders, AWM, "Setting the mind for intelligent interactive segmentation: Overview, requirements, and framework," INFORMATION PROCESSING IN MEDICAL IMAGING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1230, pp. 417-422, 1997.
Abstract:
It is widely recognized that automatic segmentation is hard, leading to
the state where user intervention cannot be avoided. In this paper we
review existing literature and propose a systematic approach for the
integration of automatic and interactive segmentation methods into one
unified process. A framework and requirements for intelligent
interactive segmentation are formulated, and an example is presented.
|
233. | Fritsch, D, Pizer, S, Yu, LY, Johnson, V, and Chaney, E, "Segmentation of medical image objects using deformable shape loci," INFORMATION PROCESSING IN MEDICAL IMAGING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1230, pp. 127-140, 1997.
Abstract:
Robust segmentation of normal anatomical objects in medical images
requires (1) methods for creating object models that adequately capture
object shape and expected shape variation across a population, and (2)
methods for combining such shape models with unclassified image data to
extract modeled objects. Described in this paper is such an approach to
model-based image segmentation, called deformable shape loci (DSL),
that has been successfully applied to 2D MR slices of the brain
ventricle and CT slices of abdominal organs. The method combines a
model and image data by warping the model to optimize an objective
function measuring both the conformation of the warped model to the
image data and the preservation of local neighbor relationships in the
model. Methods for forming the model and for optimizing the objective
function are described.
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234. | Todd-Pokropek, A, "How to find the surface when you are drowning in data: boundary conditions and constraints in medical image processing," PHYSICA MEDICA, vol. 13, pp. 197-202, 1997.
Abstract:
A major problem with many current techniques in medical imaging is the
sheer volume of data of the results; examples are in spiral CT, MRI
especially functional imaging, SPECT and PET. In general the data are
n-D, often 3-D plus time. Such data are hard to visualise without
compression, specifically some kind of multi-dimensional projection to
reduce dimensionality, for example reducing the n-D to a 2-D image.
Both linear and non-linear operations can be considered, and two
classes of method are important: data driven and hypothesis driven.
Illustrative of data driven methods is principal component analysis
(and factor analysis) where from the statistical aim of reducing
correlation, axes in the multi-dimensional space can be defined for the
projection operation. Unfortunately, in practice, a pure statistical
method does not generally map well on to expected physiological
functions (or models), and some kind of oblique rotation is required,
based on the choice of appropriate constraints such as that of
positivity. Hypothesis driven methods are all implicitly or explicitly
based on models. Thus associating data driven and hypothesis driven ap
preaches leads to constrained statistical data (image) processing.
Examples are shown as used in nuclear medicine and MRI. Another
important problem considered is that of multi-modality image
registration and fusion. Although many methods exist, all based on the
minimization of an appropriate distance functions between two image
data sets, additional constraints are required when the images are not
too similar. This leads to the idea of using mutual information as a
distance measure, and imposing constraints by means of cluster analysis
of the n-dimensional feature space. Finally, in the analysis of such
data, tests against reference data sets (atlases) are required,
normally requiring warping the data sets in space, for example by the
use of optic flow, or some kind of diffusion equation. Again, the
boundary values for the method need to be defined with respect to
medical knowledge, a further good example of data driven algorithms
supervised using clinical constraints or models.
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235. | Gunn, SR, and Nixon, MS, "Robust snake implementation; A dual active contour," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 19, pp. 63-68, 1997.
Abstract:
A conventional active contour formulation suffers difficulty in
appropriate choice of an initial contour and values of parameters.
Recent approaches have aimed to resolve these problems but can
compromise other performance aspects. To relieve the problem in
initialization, we use a dual active contour, which is combined with a
local shape model to improve the parameterization. One contour expands
from inside the target feature, the other contracts from the outside.
The two contours are interlinked to provide a balanced technique with
an ability to reject ''weak'' local energy minima.
|
236. | Tagare, HD, "Deformable 2-D template matching using orthogonal curves," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 108-117, 1997.
Abstract:
In this paper a new formulation of the two-dimensional (2-D) deformable
template matching problem is proposed. It uses a lower-dimensional
search space than conventional methods by precomputing extensions of
the deformable template along orthogonal curves. The reduction in
search space allows the use of dynamic programming to obtain globally
optimal solutions and reduces the sensitivity of the algorithm to
initial placement of the template, Further, the technique guarantees
that the result is a curve which does not collapse to a point in the
absence of strong image gradients and is always nonself intersecting.
Examples of the use of the technique on real-world images and in
simulations at low signal-to-noise ratios (SNR's) are also provided.
|
237. | Zhu, Y, and Yan, H, "Computerized tumor boundary detection using a Hopfield neural network," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 55-67, 1997.
Abstract:
In this paper, we present a new approach for detection of brain tumor
boundaries in medical images using a Hopfield neural network. The
boundary detection problem is formulated as an optimization process
that seeks the boundary points to minimize an energy functional based
on an active contour model, A modified Hopfield network is constructed
to solve the optimization problem, Taking advantage of the collective
computational ability and energy convergence capability of the Hopfield
network, our method produces the results comparable to those of
standard ''snakes''-based algorithms, but it requires less computing
time, With the parallel processing potential of the Hopfield network,
the proposed boundary detection can be implemented for real time
processing, Experiments on different magnetic resonance imaging (MRI)
data sets show the effectiveness of our approach.
|
238. | Sandor, S, and Leahy, R, "Surface-based labeling of cortical anatomy using a deformable atlas," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 16, pp. 41-54, 1997.
Abstract:
We describe a computerized method to automatically find and label the
cortical surface in three-dimensional (3-D) magnetic resonance (MR)
brain images, The approach we take is to model a prelabeled brain atlas
as a physical object and give it elastic properties, allowing it to
warp itself onto regions in a preprocessed image. Preprocessing
consists of boundary-finding and a morphological procedure which
automatically extracts the brain and sulci from an MR image and
provides a smoothed representation of the brain surface to which the
deformable model can rapidly converge, Our deformable models are
energy-minimizing elastic surfaces that can accurately locate image
features, The models are parameterized with 3-D bicubic B-spline
surfaces, We design the energy function such that cortical fissure
(sulci) points on the model are attracted to fissure points on the
image and the remaining model points are attracted to the brain
surface, A conjugate gradient method minimizes the energy function,
allowing the model to automatically converge to the smoothed brain
surface, Finally, labels are propagated from the deformed atlas onto
the high-resolution brain surface.
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239. | Sato, Y, Chen, J, Zoroofi, RA, Harada, N, Tamura, S, and Shiga, T, "Automatic extraction and measurement of leukocyte motion in microvessels using spatiotemporal image analysis," IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 44, pp. 225-236, 1997.
Abstract:
This paper describes a computer vision system for the automatic
extraction and velocity measurement of moving leukocytes that adhere to
microvessel walls from a sequence of images, The motion of these
leukocytes can be visualized as motion along the wall contours, We use
the constraint that the leukocytes move along the vessel wall contours
to generate a spatiotemporal image, and the leukocyte motion is then
extracted using the methods of spatiotemporal image analysis, The
generated spatiotemporal image is processed by a special-purpose
orientation-selective filter and a subsequent grouping process newly
developed for this application. The orientation-selective filter is
designed by considering the particular properties of the spatiotemporal
image in this application in order to enhance only the traces of
leukocytes. In the subsequent grouping process, leukocyte trace
segments are selected and grouped among all the segments obtained by
simple thresholding and skeletonizing operations, We show
experimentally that the proposed method can stably extract leukocyte
motion.
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240. | Matsumoto, S, Asato, R, Okada, T, and Konishi, J, "Intracranial contour extraction with active contour models," JMRI-JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 7, pp. 353-360, 1997.
Abstract:
A novel image processing scheme for extracting the intracranial
contours in axial magnetic resonance data sets is proposed. The scheme
incorporates the method of active contour models, a recently introduced
paradigm for contour extraction. Its performance is nearly ideal for
T2-weighted images. Although the performances for
proton-density-weighted images and T1-weighted images drop slightly,
qualitatively satisfactory extraction still can be obtained for
T1-weighted images. Due to high degree of automation, the scheme should
help speed up some image processing applications that require the
presegmentation of the intracranial cavity.
|
241. | Tek, H, and Kimia, BB, "Volumetric segmentation of medical images by three-dimensional bubbles," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 65, pp. 246-258, 1997.
Abstract:
The segmentation of structure from images is an inherently difficult
problem in computer vision and a bottleneck to its widespread
application, e.g., in medical imaging, This paper presents an approach
for integrating local evidence such as regional homogeneity and edge
response to form global structure for figure-ground segmentation. This
approach is motivated by a shock-based morphogenetic language, where
the growth of four types of shocks results in a complete description of
shape, Specifically, objects are randomly hypothesized in the form of
fourth-order shocks (seeds) which then grow, merge, split, shrink, and,
in general, deform under physically motivated ''forces,'' but slow down
and come to a halt near differential structures. Two major issues arise
in the segmentation of 3D images using this approach. First, it is
shown that the segmentation of 3D images by 3D bubbles is superior to a
slice-by-slice segmentation by 2D bubbles or by ''21/2D bubbles'' which
are inherently 2D but use 3D information for their deformation.
Specifically, the advantages lie in an intrinsic treatment of the
underlying geometry and accuracy of reconstruction. Second, gaps and
weak edges, which frequently present a significant problem for 2D and
3D segmentation, are regularized by curvature-dependent curve and
surface deformations which constitute diffusion processes, The 3D
bubbles evolving in the 3D reaction-diffusion space are a powerful tool
in the segmentation of medical and other images, as illustrated for
several realistic examples. (C) 1997 Academic Press.
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242. | Neuenschwander, W, Fua, P, Szekely, G, and Kubler, O, "Velcro surfaces: Fast initialization of deformable models," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 65, pp. 237-245, 1997.
Abstract:
Even though methods based on the use of deformable models have become
prevalent, the quality of their output depends critically on the
model's initial state, The issue of initializing such models, however,
has not received much attention even though it is often key to the
implementation of a truly useful system.
We therefore present a new approach to segmentation of
three-dimensional (3-D) shapes that initializes and then optimizes a
3-D surface model given only the data and a very small number of 3-D
seed points and corresponding surface normals. This is a valuable
capability for medical, robotic, and cartographic applications where
such seed points can be naturally supplied, In effect, the surface
model is clamped onto the object boundary in a manner reminiscent of
Velcro being closed. Applications of the developed method to stereo
imagery and to volumetric medical data are demonstrated. (C) 1997
Academic Press.
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243. | Brand, M, "Physics-based visual understanding," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 65, pp. 192-205, 1997.
Abstract:
An understanding of a scene's causal physics-how scene elements
interact and respond to forces-is a precondition to reasoning about how
the scene came to be, how it may evolve in time, and how it will
respond to manipulation. We propose a computationally inexpensive
method for recovering causal structure from images, in which a scene
model is built incrementally through interleaved sensing and analysis.
Reasoning uses generic qualitative knowledge about rigid-body
interactions, reusable between domains and similar to concepts thought
to be acquired or activated during child development. Causal constraint
propagation reveals anomalous degrees of freedom in the scene model;
prediction yields sensory plans to resolve them, Sensing operations are
highly directed and local in scope, e.g., visual routines and
proprioception. Inference depth and the number of pixels ''touched''
are bounded by the complexity of the scene. We present algorithms and
semantics that have been successfully reused in several domains of
highly structured scenes; in particular we detail a vision system that
reverse-engineers machines. (C) 1997 Academic Press.
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244. | Nastar, C, Moghaddam, B, and Pentland, A, "Flexible images: Matching and recognition using learned deformations," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 65, pp. 179-191, 1997.
Abstract:
We describe a novel technique for matching and recognition based on
deformable intensity surfaces which incorporates both the shape (x, y)
and the texture (I(x, y)) components of a 2D image. Specifically, the
intensity surface is modeled as a deformable 3D mesh in (x, y, I(x, y))
space which obeys Lagrangian dynamics. Using an efficient technique for
matching two surfaces (in terms of the analytic modes of vibration), we
can obtain a dense correspondence field (or 3D warp) between two
images, Furthermore, we use explicit statistical learning of the class
of valid deformations in order to provide a priori knowledge about
object-specific deformations, The resulting formulation leads to a
compact representation based on the physically-based modes of
deformation as well as the statistical modes of variation observed in
actual training data. We demonstrate the power of this approach with
experiments utilizing image matching, interpolation of missing data,
and image retrieval in a large face database. (C) 1997 Academic Press.
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245. | Faugeras, O, and Keriven, R, "Level set methods and the stereo problem," SCALE-SPACE THEORY IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1252, pp. 272-283, 1997.
Abstract:
We present a novel geometric approach for solving the stereo problem
for an arbitrary number of images (greater than or equal to 2). It is
based upon the definition of a variational principle that must be
satisfied by the surfaces of the objects in the scene and their images.
The Euler-Lagrange equations which are deduced from the variational
principle provide a set of PDE's which are used to deform an initial
set of surfaces which then move towards the objects to be detected. The
level set implementation of these PDE's potentially provides an
efficient and robust way of achieving the surface evolution and to deal
automatically with changes in the surface topology during the
deformation, i.e. to deal with multiple objects. Results of a two
dimensional implementation of our theory are presented on synthetic and
real images.
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246. | Pardo, JM, Cabello, D, and Heras, J, "A snake for model-based segmentation of biomedical images," PATTERN RECOGNITION LETTERS, vol. 18, pp. 1529-1538, 1997.
Abstract:
In this work we present a snake based approach for the segmentation of
images of computerized tomography (CT) scans, We introduce a new term
for the internal energy and another one for external energy which solve
common problems associated with classical snakes in this type of
images. A simplified minimizing method is also presented. (C) 1997
Elsevier Science B.V.
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247. | Jones, TN, and Metaxas, DN, "Automated 3D segmentation using deformable models and fuzzy affinity," INFORMATION PROCESSING IN MEDICAL IMAGING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1230, pp. 113-126, 1997.
Abstract:
We have developed an algorithm for segmenting objects with closed,
non-intersecting boundaries, such as the heart and the lungs, that is
independent of the imaging modality used (e.g., MRI, CT,
echocardiography). Our method is automatic and requires as
initialization a single pixel/voxel within the boundaries of the
object. Existing segmentation techniques either require much more
information during initialization, such as an approximation to the
object's boundary, or are not robust to the types of noisy data
encountered in the medical domain. By integrating region-based and
physics-based modeling techniques we have devised a hybrid design that
overcomes these limitations. In our experiments we demonstrate across
imaging modalities, that this integration automates and significantly
improves the object boundary detection results. This paper focuses on
the application of our method to 3D datasets.
|
248. | Vaillant, M, and Davatzikos, C, "Mapping the cerebral sulci: Application to morphological analysis of the cortex and to non-rigid registration," INFORMATION PROCESSING IN MEDICAL IMAGING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1230, pp. 141-154, 1997.
Abstract:
We propose a methodology for extracting parametric representations of
the cerebral sulci from magnetic resonance images, and we consider its
application to two medical imaging problems: quantitative morphological
analysis and spatial normalization and registration of brain images.
Our methodology is based on deformable models utilizing characteristics
of the cortical shape. Specifically, a parametric representation of a
sulcus is determined by the motion of an active contour along the
medial surface of the corresponding cortical fold. The active contour
is initialized along the outer boundary of the brain, and deforms
toward the deep edge of a sulcus under the influence of an external
force field restricting it to lie along the medial surface of the
particular cortical fold. A parametric representation of the surface is
obtained as the active contour traverses the sulcus. In this paper we
present results of this methodology and its applications.
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249. | Sjogreen, K, Ljungberg, M, Erlandsson, K, Floreby, L, and Strand, SE, "Registration of abdominal CT and SPECT images using Compton scatter data," INFORMATION PROCESSING IN MEDICAL IMAGING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1230, pp. 232-244, 1997.
Abstract:
The present study investigates the possibility to utilize Compton
scatter data for registration of abdominal SPECT images. A method for
registration to CT is presented, based on principal component analysis
and cross-correlation of binary images representing the interior of the
patient. Segmentation of scatter images is performed with two methods,
thresholding and a deformable contour method. To achieve similarity of
organ positions between scans, a positioning device is applied to the
patient. Evaluation of the registration accuracy is performed with a) a
I-131 phantom study, b) a Monte Carlo simulation study of an
anthropomorphic phantom, and c) a I-123 patient trial. For a) r.m.s.
distances between positions that should be equal in CT and SPECT are
obtained to 1.0+/-0.7 mm, which thus for a rigid object is at sub pixel
level. From b) results show that r.m.s. distances depend on the slice
activity distribution. With a symmetrical distribution deviations are
in the order of 5 mm. In c) distances between markers on the patient
boundary an at the maximum 16 mm and on an average 10 mm. It is
concluded that by utilizing the available Compton scatter data,
valuable positioning information is achieved. that can be used for
registration of SPECT images.
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250. | Vilarino, DL, Cabello, D, Mosquera, A, and Pardo, JM, "Application of a multilayer discrete-time CNN to deformable models," BIOLOGICAL AND ARTIFICIAL COMPUTATION: FROM NEUROSCIENCE TO TECHNOLOGY, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1240, pp. 1193-1202, 1997.
Abstract:
In this work Cellular Neural Networks are applied to image analysis
techniques as a deformable models. To this end the problem is
considered based on a discrete-time CNN with cyclic templates and
time-variant external inputs. The appropriateness for a VLSI
implementation and massively parallel computing of CNNs will permit a
considerable improvement in processing speed with respect to the
clasical active contours approaches.
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1998 |
251. | Finet, G, Maurincomme, E, Reiber, JHC, Savalle, L, Magnin, I, and Beaune, J, "Evaluation of an automatic intraluminal edge detection technique for intravascular ultrasound images," JAPANESE CIRCULATION JOURNAL-ENGLISH EDITION, vol. 62, pp. 115-121, 1998.
Abstract:
Intravascular ultrasound (IVUS) imaging enables detailed analysis and
precise measurements of vascular cross-sections. However, to achieve a
reduction in the existing level of observer variability requires the
development of quantitative IVUS. We have developed a fully automatic
intraluminal edge detection technique, based on adaptive active contour
models and called ADDER (adaptive damping dependent on echographic
regions) that allows the quantitation of the intraluminal
cross-sectional area (ICSA). Using a 30-MHz mechanically rotated
transducer mounted at the tip of a 3.5-F catheter, 58 normal and
pathologic arterial segments (from coronary, renal, splenic, iliac, and
carotid arteries) were imaged in vitro. These images were analyzed by 2
experts, E1 and E2, who manually traced the intraluminal contour twice
for each image, as well as with ADDER. Intra-observer variabilities for
ICSAs were found to be excellent (-1.454+/-3.51% for E1, 0.96+/-5.4%
for E2). The inter-observer variability was 2.1+/-4.3%. The success
factor for ADDER was 89%. Its intra-observer variability was null, as
the method always finds a unique contour. The correlation between the
automatically detected ICSA and the manual ICSA was: r=0.99
(y=1.03x+0.89 mm(2)). Morphometric variations between manually and
automatically traced contours, analyzed by the centerline method, were
100+/-140 mm on average. In conclusion, the ADDER automatic contour
detection applied to IVUS images is robust and characterized by small
systematic and random errors; therefore, quantitative IVUS is a useful
tool in clinical research trials.
|
252. | Faugeras, O, and Keriven, R, "Variational principles, surface evolution, PDE's, level set methods, and the stereo problem," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 7, pp. 336-344, 1998.
Abstract:
We present a novel geometric approach for solving the stereo problem
for an arbitrary number of images (greater than or equal to 2). It is
based upon the definition of a variational principle that must be
satisfied by the surfaces of the objects in the scene and their images,
The Euler-Lagrange equations that are deduced from the variational
principle provide a set of partial differential equations (PDE's) that
are used to deform an initial set of surfaces which then move toward
the objects to he detected, The level set implementation of these PDE's
potentially provides an efficient and robust way of achieving the
surface evolution and to deal automatically with changes in the surface
topology during the deformations, i.e., to deal with multiple objects,
Results of an implementation of our theory also dealing with occlusion
and vilility are presented on sydnthetic and real images.+
|
253. | Caselles, V, Morel, JM, Sapiro, G, and Tannenbaum, A, "Introduction to the special issue on partial differential equations and geometry-driven diffusion in image processing and analysis," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 7, pp. 269-273, 1998.
Abstract:
We propose a method for the 3D segmentation and representation of
cortical folds with a special emphasis on the cortical sulci. These
cortical structures are represented using "active ribbons". Active
ribbons are built from active surfaces, which represent the median
surface of a particular sulcus filled by CSF. Sulci modeling is
obtained from MRI acquisitions (usually T1 images). The segmentation is
performed using an automatic labeling procedure to separate gyri from
sulci based on curvature analysis of the different iso-intensity
surfaces of the original MRI volume. The outer parts of the sulci are
used to initialize the convergence of the active ribbon from the outer
parts of the brain to the interior. This procedure has two advantages:
first, it permits the labeling of voxels belonging to sulci on the
external part of the brain as well as on the inside (which is often the
hardest point) and secondly, this segmentation allows 3D visualization
of the sulci in the MRI volumetric environment as well as showing the
sophisticated shapes of the cortical structures by means of isolated
surfaces. Active ribbons can be used to study the complicated shape of
the cortical anatomy, to model the variability of these structures in
shape and position, to assist nonlinear registrations of human brains
by locally controlling the warping procedure, to map brain
neurophysiological functions into morphology or even to select the
trajectory of an intra-sulci (virtual) endoscope.
|
254. | Trinder, JC, and Wang, YD, "Automatic road extraction from aerial images," DIGITAL SIGNAL PROCESSING, vol. 8, pp. 215-224, 1998.
Abstract:
The paper presents a knowledge-based method for automatic road
extraction from aerial photography and high-resolution remotely sensed
images. The method is based on Marr's theory of vision, which consists
of low-level image processing for edge detection and linking, mid-level
processing for the formation of road structure, and high-level
processing for the recognition of roads. It uses a combined control
strategy in which hypotheses are generated in a bottom-up mode and a
top-down process is applied to predict the missing road segments. To
describe road structures a generalized antiparallel pair is proposed.
The hypotheses of road segments are generated based on the knowledge of
their geometric and radiometric properties, which are expressed as
rules in Prolog. They are verified using part-whole relationships
between roads in high-resolution images and roads in low-resolution
images and spatial relationships between verified road segments. Some
results are presented in this paper. (C) 1998 Academic Press.
|
255. | Xu, CY, Pham, DL, Prince, JL, Etemad, ME, and Yu, DN, "Reconstruction of the central layer of the human cerebral cortex from MR images," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 481-488, 1998.
Abstract:
Reconstruction of the human cerebral cortex from MR images is a
fundamental step in human brain mapping and in applications such as
surgical path planning. In a previous paper, we described a method for
obtaining a surface representation of the central layer of the human
cerebral cortex using fuzzy segmentation and a deformable surface
model. This method, however, suffers from several problems. In this
paper, we significantly improve upon the previous method by using a
fuzzy segmentation algorithm robust to intensity inhomogeneities, and
using a deformable surface model specifically designed for capturing
convoluted sulci or gyri. We demonstrate the improvement over the
previous method both qualitatively and quantitatively, and show the
result of its application to six subjects. We also experimentally
validate the convergence of the deformable surface initialization
algorithm.
|
256. | Garrido, A, and De la Blanca, NP, "Physically-based active shape models: Initialization and optimization," PATTERN RECOGNITION, vol. 31, pp. 1003-1017, 1998.
Abstract:
In this paper we describe a new approach for 2-D object segmentation
using an automatic method applied on images with problems as partial
information, overlapping objects, many objects in a single scene,
severe noise conditions and locating objects with a very high degree of
deformation. We use a physically-based shape model to obtain a
deformable template, which is defined on a canonical orthogonal
coordinate system. The proposed methodology works starting from the
output of an edge detector, which is processed to automatically obtain
an approximation of the shape. The final estimation of the shapes is
obtained fitting a deformable template model, which is defined on a
learned surface of deformation. Results from biological images are
presented. (C) 1998 Pattern Recognition Society. Published by Elsevier
Science Ltd. All rights reserved.
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257. | Falcao, AX, Udupa, JK, Samarasekera, S, Sharma, S, Hirsch, BE, and Lotufo, RDA, "User-steered image segmentation paradigms: Live wire and live lane," GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 60, pp. 233-260, 1998.
Abstract:
In multidimensional image analysis, there are, and will continue to be,
situations wherein automatic image segmentation methods fail, calling
for considerable user assistance in the process. The main goals of
segmentation research for such situations ought to be (i) to provide
effective control to the user on the segmentation process while it is
being executed, and (ii) to minimize the total user's time required in
the process. With these goals in mind, we present in this paper two
paradigms, referred to as live wire and live lane, for practical image
segmentation in large applications. For both approaches, we think of
the pixel vertices and oriented edges as forming a graph, assign a set
of features to each oriented edge to characterize its "boundariness,"
and transform feature values to costs. We provide training facilities
and automatic optimal feature and transform selection methods so that
these assignments can be made with consistent effectiveness in any
application. In live wire, the user first selects an initial point on
the boundary. For any subsequent point indicated by the cursor, an
optimal path from the initial point to the current point is found and
displayed in real time. The user thus has a live wire on hand which is
moved by moving the cursor, If the cursor goes close to the boundary,
the live wire snaps onto the boundary. At this point, if the live wire
describes the boundary appropriately, the user deposits the cursor
which now becomes the new starting point and the process continues. A
few points (live-wire segments) are usually adequate to segment the
whole 2D boundary. in live lane, the user selects only the initial
point. Subsequent points are selected automatically as the cursor is
moved within a lane surrounding the boundary whose width changes as a
function of the speed and acceleration of cursor motion. Live-wire
segments are generated and displayed in real time between successive
points. The users get the feeling that the curve snaps onto the
boundary as and while they roughly mark in the vicinity of the boundary.
We describe formal evaluation studies to compare the utility of the new
methods with that of manual tracing based on speed and repeatability of
tracing and on data taken from a large ongoing application. The studies
indicate that the new methods are statistically significantly more
repeatable and 1.5-2.5 times faster than manual tracing. (C) 1998
Academic Press.
|
258. | Bardinet, E, Cohen, LD, and Ayache, N, "A parametric deformable model to fit unstructured 3D data," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 71, pp. 39-54, 1998.
Abstract:
In many computer vision and image understanding problems, it is
important to find a smooth surface that fits a set of given
unstructured 3D data. Although approaches based on general deformable
models give satisfactory results, in particular a local description of
the surface, they involve large linear systems to solve when dealing
with high resolution 3D images. The advantage of parametric deformable
templates like superquadrics is their small number of parameters to
describe a shape. However, the set of shapes described by superquadrics
is too limited to approximate precisely complex surfaces. This is why
hybrid models have been introduced to refine the initial approximation.
This article introduces a deformable superquadric model based on a
superquadric fit followed by a free-form deformation (FFD) to fit
unstructured 3D points. At the expense of a reasonable number of
additional parameters, free-form deformations provide a much closer fit
and a volumetric deformation field. We first present the mathematical
and algorithmic details of the method. Then, since we are mainly
concerned with applications for medical images, we present a medical
application consisting in the reconstruction of the left ventricle of
the heart from a number of various 3D cardiac images. The extension of
the method to track anatomical structures in spatio-temporal images (4D
data) is presented in a companion article [9]. (C) 1998 Academic Press.
|
259. | Snel, JG, Venema, HW, and Grimbergen, CA, "Detection of the carpal bone contours from 3-D MR images of the wrist using a planar radial scale-space snake," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 17, pp. 1063-1072, 1998.
Abstract:
In this paper we consider the problems encountered when applying snake
models to detect the contours of the carpal bones in 3-D MR images of
the wrist, In order to improve the performance of the original snake
model introduced by Kass [1], we propose a new image force based on
one-dimensional (1-D) second-order Gaussian filtering and contrast
equalization,
The improved snake is less sensitive to model initialization and has no
tendency to cut off contour sections of high curvature, because 1-D
radial scale-space relaxation is used, Contour orientation is used to
minimize the influence of neighboring image structures. Due to 1-D
contrast equalization an intensity insensitive measure of external
energy is obtained. As a consequence a good balance between internal
and external energetic contributions of the snake is established, which
also improves convergence.
By incorporating this new image force into the snake model, we succeed
in accurate contour detection, even when relatively high noise levels
are present and when the contrast varies along the contours of the
bones.
|
260. | Lam, KM, and Yan, H, "An analytic-to-holistic approach for face recognition based on a single frontal view," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 20, pp. 673-686, 1998.
Abstract:
In this paper, we propose an analytic-to-holistic approach which can
identify faces at different perspective variations. The database for
the test consists of 40 frontal-view faces. The first step is to locate
15 feature points on a face. A head model is proposed, and the rotation
of the face can be estimated using geometrical measurements. The
positions of the feature points are adjusted so that their
corresponding positions for the frontal view are approximated. These
feature points are then compared with the feature points of the faces
in a database using a similarity transform. In the second step, we set
up windows for the eyes, nose, and mouth. These feature windows are
compared with those in the database by correlation. Results show that
this approach can achieve a similar level of performance from different
viewing directions of a face. Under different perspective variations,
the overall recognition rates are over 84 percent and 96 percent for
the first and the first three likely matched faces, respectively.
|
261. | Cheng, D, Mercer, RE, Barron, JL, and Joe, P, "Tracking severe weather storms in Doppler radar images," INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, vol. 9, pp. 201-213, 1998.
Abstract:
We describe an automatic storm-tracking system to help with the
forecasting of severe storms. in this article, we present the concepts
of fuzzy point, fuzzy vector, fuzzy length of a fuzzy vector, and fuzzy
angle between two nonzero fuzzy vectors, that are used in our tracking
algorithm. These concepts are used to overcome some of the limitations
of our previous work, where fixed center-of-mass storm centers did not
provide smooth tracks over time, while at the same time, their
detection was very threshold sensitive. Our algorithm uses region
splitting with dynamic thresholding to determine storm masses in
Doppler radar intensity images. We represent the center of a
hypothesized storm using a fuzzy point. These fuzzy storm centers are
then tracked over time using an incremental relaxation algorithm. We
have developed a visualization program using the X11 Athena toolkit for
our storm visualization tool. The algorithm was tested on seven real
radar image sequences obtained from the Atmospheric Environment Service
radar station at King City, Ontario, Canada. We can obtain storm tracks
that are long and smooth and which closely match an expert
meteorologist's perception. (C) 1998 John Wiley & Sons, Inc. Int J
Imaging Syst Technol, 9, 201-213, 1998.
|
262. | Grenander, U, and Miller, MI, "Computational anatomy: An emerging discipline," QUARTERLY OF APPLIED MATHEMATICS, vol. 56, pp. 617-694, 1998.
Abstract:
This paper studies mathematical methods in the emerging new discipline
of Computational Anatomy. Herein we formalize the Brown/Washington
University model of anatomy following the global pattern theory
introduced in [1, 2], in which anatomies are represented as deformable
templates, collections of 0, 1, 2, 3-dimensional manifolds. Typical
structure is carried by the template with the variabilities
accommodated via the application of random transformations to the
background manifolds. The anatomical model is a quadruple (Omega, H, I,
P), the background space Omega = boolean ORalpha M-alpha of 0, 1, 2,
3-dimensional manifolds, the set of diffeomorphic transformations on
the background space H : Omega <-> Omega, the space of idealized
medical imagery I, and P the family of probability measures on H. The
group of diffeomorphic transformations H is chosen to be rich enough so
that a large family of shapes may be generated with the topologies of
the template maintained. For normal anatomy one deformable template is
studied, with (Omega, H, I) corresponding to a homogeneous space [3],
in that it can be completely generated from one of its elements, I =
HItemp,I-temp is an element of I. For disease, a family of templates
boolean ORalphaItempalpha are introduced of perhaps varying dimensional
transformation classes. The complete anatomy is a collection of
homogeneous spaces I-total = boolean ORalpha(I-alpha,H-alpha).
There are three principal components to computational anatomy studied
herein.
(1) Computation of large deformation maps: Given any two elements I, I'
is an element of I in the same homogeneous anatomy (Omega, H, I),
compute diffeomorphisms h from one anatomy to the other I
(h-1)reversible arrow(h) I'. This is the principal method by which
anatomical structures are understood, transferring the emphasis from
the images I is an element of I to the structural transformations h is
an element of H that generate them.
(2) Computation of empirical probability laws: Given populations of
anatomical imagery and diffeomorphisms between them I h(n-1)reversible
arrow(hn) I-n, n = 1, . . . , N, generate probability laws P is an
element of P on H that represent the anatomical variation reflected by
the observed population of diffeomorphisms h(n), n = 1,..., N.
(3) Inference and disease testing: Within the anatomy (Omega, H, I, P),
perform Bayesian classification and testing for disease and anomaly.
|
263. | Long, Q, Xu, XY, Collins, MW, Bourne, M, and Griffith, TM, "Magnetic resonance image processing and structured grid generation of a human abdominal bifurcation," COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol. 56, pp. 249-259, 1998.
Abstract:
Magnetic resonance angiography (MRA) offers a non-invasive approach to
the acquisition of anatomically accurate human arterial structure.
Combining the latest computational fluid dynamics (CFD) techniques with
clinical data from MRA, the detailed haemodynamics information in the
human circulation system can be obtained. In this paper, a novel
computer method is presented, which generates automatically a
computational grid for a human abdominal bifurcation from a set of
conventional MRA images. The method covers the complete sequence from
MR image segmentation, 3-D model construction, grid generation, to grid
quality evaluation. Results demonstrate that the computer program
developed is capable of generating a good quality grid for human
arterial bifurcations from MRA images with minimum user. input. The
resultant grid can be used directly for further computer simulation of
the flow. (C) 1998 Elsevier Science Ireland Ltd. All rights reserved.
|
264. | Morrow-Tesch, J, Dailey, JW, and Jiang, H, "A video data base system for studying animal behavior," JOURNAL OF ANIMAL SCIENCE, vol. 76, pp. 2605-2608, 1998.
Abstract:
Classification of farm animal behavior is based on oral or written
descriptions of the activity in which the animal is engaged. The
quantification of animal behavior for research requires that
individuals recognize and code the behavior of the animal under study.
The classification of these behaviors can be subjective and may differ
among observers. Illustrated guides to animal behavior do not convey
the motion associated with most behaviors. Video-based guides offer a
method of quantifying behaviors with real-time demonstrations of the
components that make up a behavior. An animal behavior encyclopedia has
been developed to allow searching and viewing of defined
(video-recorded) behaviors on the Internet. This video data base is
being developed to initiate a system that automatically extracts animal
motion information from an input animal activity video clip using a
multiobject tracking and reasoning system. Eventually, the extracted
information will be analyzed and described using standard animal
behavior definitions (the behavior encyclopedia). The intended
applications of the behavior encyclopedia and video tracking system are
1) an accessible data base for defining and illustrating behaviors for
both research and teaching and 2) to further automate the collection of
animal behavior data.
|
265. | Hu, YL, Rogers, WJ, Coast, DA, Kramer, CM, and Reichek, N, "Vessel boundary extraction based on a global and local deformable physical model with variable stiffness," MAGNETIC RESONANCE IMAGING, vol. 16, pp. 943-951, 1998.
Abstract:
Reliable and efficient vessel cross-sectional boundary extraction is
very important for many medical magnetic resonance (MR) image studies.
General purpose edge detection algorithms often fail for medical MR
images processing due to fuzzy boundaries, inconsistent image contrast,
missing edge features, and the complicated background of MR images. In
this regard, we present a vessel cross-sectional boundary extraction
algorithm based on a global and local deformable model with variable
stiffness. With the global model, the algorithm can handle relatively
large vessel position shifts and size changes. The local deformation
with variable stiffness parameters enable the model to stay right on
edge points at the location where edge features are strong and at the
same time, fit a smooth contour at the location where edge features are
missing, Directional gradient information is used to help the model to
pick correct edge segments. The algorithm was used to process MR cine
phase-contrast images of the aorta from 20 volunteers (over 500 images)
with excellent results. (C) 1998 Elsevier Science Inc.
|
266. | Wolberg, G, "Image morphing: a survey," VISUAL COMPUTER, vol. 14, pp. 360-372, 1998.
Abstract:
Image morphing has received much attention in recent years. It has
proven to be a powerful tool for visual effects in film and television,
enabling the fluid transformation of one digital image into another.
This paper surveys the growth of this field and describes recent
advances in image morphing in terms of feature specification, warp
generation methods, and transition control. These areas relate to the
ease of use and quality of results. We describe the role of radial
basis functions, thin plate splines, energy minimization, and
multilevel free-form deformations in advancing the state-of-the-art in
image morphing. Recent work on a generalized framework for morphing
among multiple images is described.
|
267. | Gao, PS, and Sederberg, TW, "A work minimization approach to image morphing," VISUAL COMPUTER, vol. 14, pp. 390-400, 1998.
Abstract:
We present an algorithm for morphing two images, often with little or
no user interaction. For two similar images (such as different faces
against a neutral background), the algorithm generally can create a
pleasing morph completely automatically. The algorithm seeks to
minimize the work needed to deform one image into the other. Work is
defined as a function of the amount of warping and recoloration. We
invoke a hierarchical method for finding a minimal work solution.
Anchor point constraints are satisfied by penalties imposed on
deformations that disobey these constraints. Good results can be
obtained in less than 10 s for 256x256 images.
|
268. | Tang, CK, Medioni, G, and Duret, F, "Automatic, accurate surface model inference for dental CAD/CAM," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 732-742, 1998.
Abstract:
Dental CAD/CAM offers the prospects of drastically reducing the time to
provide service to patients, with no compromise on quality. Given the
state-of-the-art in sensing, design, and machining, an attractive
approach is to have a technician generate a restorative design in wax,
which can then be milled by a machine in porcelain or titanium. The
difficulty stems from the inherent outlier noise in the measurement
phase. Traditional techniques remove noise at the cost of smoothing,
degrading discontinuities such as anatomical lines which require
accuracy up to 5 to 10 mu m to avoid artifacts. This paper presents an
efficient method for the automatic and accurate data validation and 3-D
shape inference from noisy digital dental measurements. The input
consists of 3-D points with spurious samples, as obtained from a
variety of sources such as a laser scanner or a stylus probe. The
system produces faithful smooth surface approximations while preserving
critical curve features such as grooves and preparation lines. To this
end, we introduce the Tensor Voting technique, which efficiently
ignores noise, infers smooth structures, and preserves underlying
discontinuities. This method is non-iterative, does not require initial
guess, and degrades gracefully with spurious noise, missing and
erroneous data. We show results on real and complex data.
|
269. | Jiang, HT, and Elmagarmid, AK, "Spatial and temporal content-based access to hypervideo databases," VLDB JOURNAL, vol. 7, pp. 226-238, 1998.
Abstract:
Providing content-based video query, retrieval and browsing is the most
important goal of a video database management system (VDBRIS). Video
data is unique not only in terms of its spatial and temporal
characteristics, but also in the semantic associations manifested by
the entities present in the video. This paper introduces a novel video
data model called Logical Hypervideo Data,Model. In addition to
multilevel video abstractions, the model is capable of representing
video entities that users are interested in (defined as hot objects)
and their semantic associations with other logical video abstractions,
including hot objects themselves. The semantic associations are modeled
as video hyperlinks and video data with such property are called
hypervideo. Video hyperlinks provide a flexible and effective way of
browsing video data. Based on the proposed model, video queries can be
specified with both temporal and spatial constraints, as well as with
semantic descriptions of the video data. The characteristics of hot
objects' spatial and temporal relations and efficient evaluation of
them are also discussed. Some query examples are given to demonstrate
the expressiveness of the video data model and query language. Finally,
we describe a modular video database system architecture that our
web-based prototype is based on.
|
270. | MacDonald, D, Avis, D, and Evans, AC, "Proximity constraints in deformable models for cortical surface identification," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 650-659, 1998.
Abstract:
Automatic computer processing of large multi-dimensional images such as
those produced by magnetic resonance imaging (MRI) is greatly aided by
deformable models. A general method of deforming polyhedra is presented
here, with two novel features. Firstly, explicit prevention of
non-simple (self-intersecting) surface geometries is provided, unlike
conventional deformable models which merely discourage such behaviour.
Secondly, simultaneous deformation of multiple surfaces with
inter-surface proximity constraints provides a greater facility for
incorporating model-based constraints into the process of image
recognition. These two features are used advantageously to
automatically identify the total surface of the cerebral cortical gray
matter from normal human MR images, accurately locating the depths of
the sulci even where under-sampling in the image obscures the
visibility of sulci. A large number of individual surfaces (N=151) are
created and a spatial map of the mean and standard deviation of the
cerebral cortex and the thickness of cortical gray matter are
generated. Ideas for further work are outlined.
|
271. | Wink, O, Niessen, WJ, and Viergever, MA, "Fast quantification of abdominal aortic aneurysms from CTA volumes," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 138-145, 1998.
Abstract:
A method is presented which aids the clinician in obtaining
quantitative measurements of an abdominal aortic aneurysm from a CTA
volume. These measurements are needed in the preoperative evaluation of
candidates for minimally invasive aneurysmal repair. The user
initializes starting points in the iliac artery, Subsequently, an
iterative tracking procedure outlines the central lumen line in the
aorta and the iliac arteries. Quantitative measurements on vessel
morphology are performed in the planes perpendicular to the vessel
axis. The entire process is performed in less than one minute on a
standard workstation. In addition to the presentation of the calculated
measures, a 3D view of the vessels is generated. This allows for
interactive inspection of the vasculature and the tortuosity of the
vessels.
|
272. | Positano, V, Santarelli, MF, Landini, L, and Benassi, A, "Fast and quantitative analysis of 4D cardiac images using a SMP architecture," APPLIED PARALLEL COMPUTING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1541, pp. 447-451, 1998.
Abstract:
In the present research a parallel algorithm for medical image
processing has been proposed, which allows 3D quantitative analysis of
left ventricular cardiac wall motion in real time. It is a fundamental
task in evaluating a lot of indexes useful to perform diagnosis of
important diseases. However, such analysis involves expensive tasks in
terms of computational time: tridimensional segmentation and an
accurate cavity contour detection during the entire cardiac cycle. In
this paper an implementation of a dynamic quantitative analysis
algorithm on low-cost Shared Memory Processor machine is described. In
order to test the developed system in actual environment, a dynamic
sequence of 3D data volume, derived from Magnetic Resonance (MR)
cardiac images, has been processed.
|
273. | Lotjonen, J, Magnin, IE, Reissman, PJ, Nenonen, J, and Katila, T, "Segmentation of magnetic resonance images using 3D deformable models," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 1213-1221, 1998.
Abstract:
A new method to segment MR volumes has been developed. The method
matches elastically a 3D deformable prior model, describing the
structures of interest, to the MR volume of a patient. The deformation
is done using a deformation grid. Oriented distance maps are utilized
to guide the deformation process. Two alternative restrictions are used
to preserve the geometrical prior knowledge of the model. The method is
applied to extract the body, the lungs and the heart. The segmentation
is needed to build individualized boundary element models for
bioelectromagnetic inverse problem. The method is fast, automatic and
accurate. Good results have been achieved for four MR volumes tested so
far.
|
274. | Lorigo, LM, Faugeras, O, Grimson, WEL, Keriven, R, and Kikinis, R, "Segmentation of bone in clinical knee MRI using texture-based geodesic active contours," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 1195-1204, 1998.
Abstract:
This paper presents a method for automatic segmentation of the tibia
and femur in clinical magnetic resonance images of knees. Texture
information is incorporated into an active contours framework through
the use of vector-valued geodesic snakes with local variance as a
second value at each pixel, in addition to intensity. This additional
information enables the system to better handle noise and the
non-uniform intensities found within the structures to be segmented. It
currently operates independently on 2D images (slices of a volumetric
image) where the initial contour must be within the structure but not
necessarily near the boundary. These separate segmentations are stacked
to display the performance on the entire 3D structure.
|
275. | Sebastian, TB, Tek, H, Crisco, JJ, Wolfe, SW, and Kimia, BB, "Segmentation of carpal bones from 3D CT images using skeletally coupled deformable models," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 1184-1194, 1998.
Abstract:
The in vivo investigation of joint kinematics in normal and injured
wrist requires the segmentation of carpal bones from 3D (CT) images and
their registration over time. The non-uniformity of bone tissue,
ranging from dense cortical bone to textured spongy bone, the
irregular, small shape of closely packed carpel bones which move with
respect to one another, and with respect to CT resolution, augmented
with the presence of blood vessels, and the inherent blurring of CT
imaging renders the segmentation of carpal bones a challenging task.
Specifically, four characteristic difficulties are prominent: (i) gaps
or weak edges in the carpal bone surfaces. (ii) diffused edges, (iii)
textured regions, and, (iv) extremely narrow inter-bone regions. We
review the performance of statistical classification! deformable
models, region growing, and morphological operations for this
application. We then propose a model which. combines several of these
approaches in a single framework. Specifically, initialized seeds grow
in a curve evolution implementation of active contours, but where
growth is modulated by a skeletally-mediated competition between
neighboring regions, thus combining the advantages of local and global
region growing methods, region competition and active contours. This
approach effectively deals with many of the difficulties presented
above as illustrated by numerous examples.
|
276. | Poupon, F, Mangin, JF, Hasboun, D, Poupon, C, Magnin, I, and Frouin, V, "Multi-object deformable templates dedicated to the segmentation of brain deep structures," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1496, pp. 1134-1143, 1998.
Abstract:
We propose a new way of embedding shape distributions in a topological
deformable template. These distributions rely on global shape
descriptors corresponding to the 3D moment invariants. In opposition to
usual Fourier-like descriptors, they can be updated during deformations
at a relatively low cost. The moment-based distributions are included
in a framework allowing the management of several simultaneously
deforming objects. This framework is dedicated to the segmentation of
brain deep nuclei in 3D MR images. The paper focuses on the learning of
the shape distributions, on the initialization of the topological model
and on the multi-resolution energy minimization process. Results are
presented showing the segmentation of twelve brain deep structures.
|
277. | Xu, CY, and Prince, JL, "Generalized gradient vector flow external forces for active contours," SIGNAL PROCESSING, vol. 71, pp. 131-139, 1998.
Abstract:
Active contours, or snakes, are used extensively in computer vision and
image processing applications, particularly to locate object
boundaries. A new type of external force for active contours, called gi
adient vector flow (GVF) was introduced recently to address problems
associated with initialization and poor convergence to boundary
concavities. GVF is computed as a diffusion of the gradient vectors of
a gray-level or binary edge map derived from the image. In this paper,
we generalize the GVF formulation to include two spatially varying
weighting functions. This improves active contour convergence to long,
thin boundary indentations, while maintaining other desirable
properties of GVF, such as an extended capture range. The original GVF
is a special case of this new generalized GVF (GGVF) model. An error
analysis for active contour results on simulated test images is also
presented. (C) 1998 Elsevier Science B.V. All rights reserved.
|
278. | Montagnat, J, and Delingette, H, "Globally constrained deformable models for 3D object reconstruction," SIGNAL PROCESSING, vol. 71, pp. 173-186, 1998.
Abstract:
To achieve geometric reconstruction from 3D datasets two complementary
approaches have been widely used. On one hand, the deformable model
framework locally applies forces to fit the data. On the other hand,
the non-rigid registration framework computes a global transformation
minimizing the distance between a template and the data. We first show
that applying a global transformation on a surface template, is
equivalent to applying certain global forces on a deformable model.
Second, we propose a scheme which combines the registration and
free-form deformation. This globally constrained deformation scheme
allows us to control the amount of deformation from the reference shape
with a single parameter. Finally, we propose a general algorithm for
performing model-based reconstruction in a robust and accurate manner.
Examples on both range data and medical images are used to illustrate
and validate the globally constrained deformation framework. (C) 1998
Elsevier Science B.V. All rights reserved.
|
279. | Pavlidis, I, Papanikolopoulos, N, and Mavuduru, R, "Signature identification through the use of deformable structures," SIGNAL PROCESSING, vol. 71, pp. 187-201, 1998.
Abstract:
Automatic signature verification is a well-established and active
research area with numerous applications. In contrast, automatic
signature identification has been given little attention, although
there is a vast array of potential applications that could use the
signature as an identification tool. This paper presents a novel
approach to the problem of signature identification. We introduce the
use of the revolving active deformable model as a powerful way of
capturing the unique characteristics of the overall structure of a
signature. Experimental evidence as well as intuition support the idea
that the overall structure of a signature uniquely determines the
signature in the majority of cases. Our revolving active deformable
model originates from the snakes introduced in computer vision by Kass
et al., but its implementation has been tailored to the task at hand.
This computer-generated model interacts with the virtual gravity field
created by the image gradient. Ideally, the uniqueness of this
interaction mirrors the uniqueness of the signature's overall
structure. The proposed method obviates the use of a computationally
expensive segmentation approach and is parallelizable. The experiments
performed with a signature database show that the proposed method is
promising. (C) 1998 Elsevier Science B.V. All rights reserved.
|
280. | Hinshaw, KP, and Brinkley, JF, "Incorporating constraint-based shape models into an interactive system for functional brain mapping," JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, vol. 71, pp. 921-925, 1998.
Abstract:
Through intraoperative electrical stimulation mapping, it is possible
to identify sites on the surface of the brain that are essential for
language function. Interesting correlations have been found between the
distribution of these sites and behavioral traits such as verbal IQ. In
previous work, tools were developed for building a reconstruction of a
patient's cortical surface and using it to recover coordinates of
essential language sites. However, considerable expertise was required
to produce good reconstructions. This paper describes an improved
version of the mapping procedure, in which segmentation is driven by a
3-D shape model. The model-based approach provides more intuitive
control over the system, allowing a trained user to complete a surface
reconstruction and mapping in about two hours. This level of
performance makes it feasible to gather language maps for a large
number of patients, which hopefully will lead to significant new
findings about language organization in the brain.
|
281. | Gupta, K, "Motion planning for flexible shapes (systems with many degrees of freedom): a survey," VISUAL COMPUTER, vol. 14, pp. 288-302, 1998.
Abstract:
This article provides a brief tutorial-cum-overview of motion planning
for "flexible" shapes. The article takes the point of view that motion
planning for flexible shapes, in a broad sense, essentially amounts to
motion planning for systems with many degrees of freedom (dofs), a
well-studied problem in robotics. We start with the basics of motion
planning including an introduction to some key concepts, survey a
number of recent approaches to solve the motion planning for systems
with many dofs, discuss the application of some of these approaches to
motion planning for flexible shapes, and report, on some recent work in
this area.
|
282. | Brandtberg, T, and Walter, F, "Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis," MACHINE VISION AND APPLICATIONS, vol. 11, pp. 64-73, 1998.
Abstract:
This paper presents an automatic multiple-scale algorithm for
delineation of individual tree crowns in high spatial resolution
infrared colour aerial images. The tree crown contours were identified
as zero-crossings, with convex grey-level curvature, which were
computed on the intensity image for each image scale. A modified centre
of curvature was estimated for every edge segment pixel. For each
segment, these centre points formed a swarm which was modelled as a
primal sketch using an ellipse extended with the mean circle of
curvature. The model described the region of the derived tree crown
based on the edge segment at the current scale. The sketch was rescaled
with a significance value and accumulated for a scale interval. In the
accumulated sketch, a tree crown segment was grown, starting at local
peaks, under the condition that it was inside the area of healthy
vegetation in the aerial image and did not trespass into a neighbouring
crown segment. The method was evaluated by comparison with manual
delineation and with ground truth on 43 randomly selected sample plots.
It was concluded that the performance of the method is almost
equivalent to visual interpretation. On the average, seven out of ten
tree crowns were the same. Furthermore, ground truth indicated a large
number of hidden trees. The proposed technique could be used as a basic
tool in forest surveys.
|
283. | Ip, HHS, and Shen, DG, "An affine-invariant active contour model (AI-snake) for model-based segmentation," IMAGE AND VISION COMPUTING, vol. 16, pp. 135-146, 1998.
Abstract:
In this paper, we show that existing shaped-based active contour models
are not affine-invariant and we addressed the problem by presenting an
affine-invariant snake model (AI-snake) such that its energy function
are defined in terms local and global affine-invariant features. The
main characteristic of the AI-snake is that, during the process of
object extraction, the pose of the model contour is dynamically
adjusted such that it is in alignment with the current snake contour by
solving the snake-prototype correspondence problem and determining the
required affine transformation. In addition, we formulate the
correspondence matching between the snake and the object prototype as
an error minimization process between two feature vectors which capture
both local and global deformation information. We show that the
technique is robust against object deformations and complex scenes. (C)
1998 Elsevier Science B.V.
|
284. | Tupin, F, Maitre, H, Mangin, JF, Nicolas, JM, and Pechersky, E, "Detection of linear features in SAR images: Application to road network extraction," IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 36, pp. 434-453, 1998.
Abstract:
We propose a two-step algorithm for almost unsupervised detection of
linear structures, in particular, main axes in road networks, as seen
in synthetic aperture radar (SAR) images. The first step is local and
is used to extract linear features from the speckle radar image, which
are treated as road-segment candidates. We present two local line
detectors as well as a method for fusing information from these
detectors, In the second global step, we identify the real roads among
the segment candidates by defining a Markov random field (MRF) on a set
of segments, which introduces contextual knowledge about the shape of
road objects, The influence of the parameters on the road detection is
studied and results are presented for various real radar images.
|
285. | Calabi, E, Olver, PJ, Shakiban, C, Tannenbaum, A, and Haker, S, "Differential and numerically invariant signature curves applied to object recognition," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 26, pp. 107-135, 1998.
Abstract:
We introduce a new paradigm, the differential invariant signature curve
or manifold, for the invariant recognition of visual objects. A general
theorem of E. Cartan implies that two curves are related by a group
transformation if and only if their signature curves are identical. The
important examples of the Euclidean and equi-affine groups are
discussed in detail. Secondly, we show how a new approach to the
numerical approximation of differential invariants, based on suitable
combination of joint invariants of the underlying group action, allows
one to numerically compute differential invariant signatures in a fully
group-invariant manner. Applications to a variety of fundamental issues
in vision, including detection of symmetries, visual tracking, and
reconstruction of occlusions, are discussed.
|
286. | Younes, L, "Computable elastic distances between shapes," SIAM JOURNAL ON APPLIED MATHEMATICS, vol. 58, pp. 565-586, 1998.
Abstract:
We define distances between geometric curves by the square root of the
minimal energy required to transform one curve into the other. The
energy is formally defined from a left invariant Riemannian distance on
an infinite dimensional group acting on the curves, which can be
explicitly computed. The obtained distance boils down to a variational
problem for which an optimal matching between the curves has to be
computed. An analysis of the distance when the curves are polygonal
leads to a numerical procedure for the solution of the variational
problem, which can efficiently be implemented, as illustrated by
experiments.
|
287. | Fua, P, "Fast, accurate and consistent modeling of drainage and surrounding terrain," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 26, pp. 215-234, 1998.
Abstract:
We propose an automated approach to modeling drainage channels-and,
more generally, linear features that lie on the terrain-from multiple
images. It produces models of the features and of the surrounding
terrain that are accurate and consistent and requires only minimal
human intervention.
We take advantage of geometric constraints and photommetric knowledge.
First, rivers flow downhill and lie at the bottom of valleys whose
floors tend to be either V- or U-shaped. Second, the drainage pattern
appears in gray-level images as a network of linear features that can
be visually detected.
Many approaches have explored individual facets of this problem. Ours
unifies these elements in a common framework. We accurately model
terrain and features as 3-dimensional objects from several information
sources that may be in error and inconsistent with one another. This
approach allows us to generate models that are faithful to sensor data,
internally consistent and consistent with physical constraints. We have
proposed generic models that have been applied to the specific task at
hand. We show that the constraints can be expressed in a
computationally effective way and, therefore, enforced while
initializing the models and then fitting them to the data. Furthermore,
these techniques are general enough to work on other features that are
constrained by predictable forces.
|
288. | Noble, JA, Gupta, R, Mundy, J, Schmitz, A, and Hartley, RI, "High precision X-ray stereo for automated 3-D CAD-based inspection," IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, vol. 14, pp. 292-302, 1998.
Abstract:
An important challenge in industrial metrology is to provide rapid
measurement of critical three-dimensional (3-D) internal object
geometry for either inspecting high volume parts or controlling a
machining process, Existing metrological techniques are typically too
slow to meet this need or can not measure small features with high
precision.
In this paper, we present a new method that achieves fast, accurate,
internal 3-D geometry measurement based on 3-D reconstruction from a
few X-ray views of a part, Our approach utilizes an accurate camera
model for the X-ray sensor, calibration using in situ ground truth and
geometry-guided X-ray feature extraction to achieve this goal and has
been fully implemented in a prototype 3-D measurement system, We
describe a novel application of the system to CAD-based verification of
drilled hole positioning. Experimental results are given to illustrate
the precision of the system and 3-D measurement on real industrial
parts.
|
289. | Chesnaud, C, Page, V, and Refregier, P, "Improvement in robustness of the statistically independent region snake-based segmentation method of target-shape tracking," OPTICS LETTERS, vol. 23, pp. 488-490, 1998.
Abstract:
We propose a technique to increase the robustness of a snake-based
segmentation method originally introduced to track the shape of a
target with random white Gaussian intensity upon a random white
Gaussian background. Because these statistical conditions are not
always fulfilled with optronic images, we describe two improvements
that increase the field of application of this approach. We first show
that regularized whitening preprocessing allows one to apply the
original method successfully for a target with a correlated texture
upon a correlated background. We then introduce a simple multiscale
approach that increases the robustness of the segmentation against the
initialization of the snake (i.e., the initial shape used for the
segmentation). These results provide a robust and practical method for
determination of the reference image for correlation techniques. (C)
1998 Optical Society of America.
|
290. | Casadei, S, and Mitter, S, "Hierarchical image segmentation - Part I: Detection of regular curves in a vector graph," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 27, pp. 71-100, 1998.
Abstract:
The problem of edge detection is viewed as a hierarchy of detection
problems where the geometric objects to be detected (e.g., edge points,
curves, regions) have increasing complexity and spatial extent. An
early stage of the proposed hierarchy consists in detecting the regular
portions of the visible edges. The input to this stage is given by a
graph whose vertices are tangent vectors representing local and
uncertain information about the edges. A model relating the input
vector graph to the curves to be detected is proposed. An algorithm
with linear time complexity is described which solves the corresponding
detection problem in a worst-case scenario. The stability of curve
reconstruction in the presence of uncertain information and multiple
responses to the same edge is analyzed and addressed explicitly by the
proposed algorithm.
|
291. | Malassiotis, S, and Strintzis, MG, "Tracking textured deformable objects using a finite-element mesh," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol. 8, pp. 756-774, 1998.
Abstract:
This paper presents an algorithm for the estimation of the motion of
textured objects undergoing nonrigid deformations over a sequence of
images. An active mesh model, which is a finite-element deformable
membrane, is introduced in order to achieve efficient representation of
global and local deformations, The mesh is constructed using an
adaptive triangulation procedure that places more triangles over high
detail areas. Through robust least squares techniques and modal
analysis, efficient estimation of global object deformations is
achieved, based on a set of sparse displacement measurements. A local
warping procedure is then applied to minimize the intensity matching
error between subsequent images, and thus estimate local deformations,
Among the major contributions of this paper are novel techniques
developed to acquire knowledge of the object dynamics and structure
directly from the image sequence, even in the absence of prior
intelligence regarding the scene, Specifically, a coarse-to-fine
estimation scheme is first developed, which adapts the model to locally
deforming features. Subsequently, principal components modal analysis
is used to accumulate knowledge of the object dynamics. This knowledge
is finally exploited to constrain the object deformation. The problem
of tracking the model over time is addressed, and a novel
motion-compensated prediction approach is proposed to facilitate this.
A novel method for the determination of the dynamical principal axes of
deformation is developed, The experimental results demonstrate the
efficiency and robustness of the proposed scheme, which has many
potential applications in the areas of image coding, image analysis,
and computer graphics.
|
292. | Luan, JA, Stander, J, and Wright, D, "On shape detection in noisy images with particular reference to ultrasonography," STATISTICS AND COMPUTING, vol. 8, pp. 377-389, 1998.
Abstract:
We discuss the detection of a connected shape in a noisy image. Two
types of image are considered: in the first a degraded outline of the
shape is visible, while in the second the data are a corrupted version
of the shape itself. In the first type the shape is defined by a thin
outline of pixels with records that are different from those at pixels
inside and outside the shape, while in the second type the shape is
defined by its edge and pixels inside and outside the shape have
different records. Our motivation is the identification of
cross-sectional head shapes in ultrasound images of human fetuses. We
describe and discuss a new approach to detecting shapes in images of
the first type that uses a specially designed filter function that
iteratively identifies the outline pixels of the head. We then suggest
a way based on the cascade algorithm introduced by Jubb and Jennison
(1991) of improving and considerably increasing the speed of a method
proposed by Storvik (1994) for detecting edges in images of the second
type.
|
293. | Park, JS, and Han, JH, "Contour motion estimation from image sequences using curvature information," PATTERN RECOGNITION, vol. 31, pp. 31-39, 1998.
Abstract:
This paper presents a novel method of velocity field estimation for the
points on moving contours in a 2-D image sequence. The method
determines the corresponding point in a next image frame by considering
the curvature change of a given point on the contour. In traditional
methods, there are errors in optical flow estimation for the points
which have low curvature variations since those methods compute
solutions by approximating normal optical flow. The proposed method
computes optical flow vectors of contour points minimizing the
curvature changes. As a first step, snakes are used to locate smooth
curves in 2-D imagery. Thereafter, the extracted curves are tracked
continuously. Each point on a contour has a unique corresponding point
on the contour in the next frame whenever the curvature distribution of
the contour varies smoothly. The experimental results showed that the
proposed method computes accurate optical flow vectors for various
moving contours. (C) 1997 Pattern Recognition Society. Published by
Elsevier Science Ltd.
|
294. | Gunn, SR, and Nixon, MS, "Global and local active contours for head boundary extraction," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 30, pp. 43-54, 1998.
Abstract:
Active contours are an attractive choice to extract the head boundary,
for deployment within a face recognition or model-based coding
scenario. However, conventional snake approaches can suffer difficulty
in initialisation and parameterisation. A dual active contour
configuration using dynamic programming has been developed to resolve
these difficulties by using a global energy minimisation technique and
a simplified parameterisation, to enable a global solution to be
obtained. The merits of conventional gradient descent based snake
(local) approaches, and search-based (global) approaches are discussed.
In application to find head and face boundaries in front-view face
images, the new technique employing dynamic programming is deployed to
extract the inner face boundary, along with a conventional
normal-driven contour to extract the outer (head) boundary. The
extracted contours appear to offer sufficient discriminatory capability
for inclusion within an automatic face recognition system.
|
295. | Jain, AK, Zhong, Y, and Dubuisson-Jolly, MP, "Deformable template models: A review," SIGNAL PROCESSING, vol. 71, pp. 109-129, 1998.
Abstract:
In this paper, we review the recently published work on deformable
models. We have chosen to concentrate on 2D deformable models and
relate the energy minimization approaches to the Bayesian formulations.
We categorize the various active contour systems according to the
definition of the deformable model. We also present in detail one
particular formulation for deformable templates which combines edge,
texture, color and region information for the external energy and model
deformations using wavelets, splines or Fourier descriptors. We explain
how these models can be used for segmentation, image retrieval in a
large database and object tracking in a video sequence. (C) 1998
Elsevier Science B.V. All rights reserved.
|
296. | Schultz, N, and Conradsen, K, "2D vector-cycle deformable templates," SIGNAL PROCESSING, vol. 71, pp. 141-153, 1998.
Abstract:
In this paper the theory of deformable templates as a vector cycle in
2D is described. The deformable template model originated in
(Grenander, 1983) and was further investigated in (Grenander st al.,
1991). A template vector distribution is induced by parameter
distributions from transformation matrices applied to the vector cycle.
An approximation in the parameter distribution is introduced. The main
advantage by using the deformable template model is the ability to
simulate a wide range of objects constrained by e.g. their biological
variations, and thereby improve restoration, segmentation and
classification tasks. For the segmentation the Metropolis algorithm and
simulated annealing are used in a Bayesian scheme to obtain a maximum a
posteriori estimator. Different energy functions are introduced and
applied to different tasks in a case study. The energy functions are
local mean, local gradient and probability measurement. The case study
concerns estimation of meat percent in pork carcasses. Given two
cross-sectional images - one at the front and one near the ham of the
carcass - the areas of lean and fat and a muscle in the lean area are
measured automatically by the deformable templates. (C) 1998 Elsevier
Science B.V. All rights reserved.
|
297. | Elmoataz, A, Schupp, S, Clouard, R, Herlin, P, and Bloyet, D, "Using active contours and mathematical morphology tools for quantification of immunohistochemical images," SIGNAL PROCESSING, vol. 71, pp. 215-226, 1998.
Abstract:
An image segmentation method is proposed, which combines mathematical
morphology tools and active contours in two stages. First, contours are
coarsely approximated by means of morphological operators. Second,
these initial contours evolve under the influence of geometric and
grey-level information, owing to the model of active contours. The
performance of the method is evaluated according to the noise and is
compared to the watershed algorithm. Then an application is finally
presented for biomedical images of tumour tissue. (C) 1998 Elsevier
Science B.V. All rights reserved.
|
298. | Basu, S, Oliver, N, and Pentland, A, "3D lip shapes from video: A combined physical-statistical model," SPEECH COMMUNICATION, vol. 26, pp. 131-148, 1998.
Abstract:
Tracking human lips in video is an important but notoriously difficult
task. To accurately recover their motions in 3D from any head pose is
an even more challenging task, though still necessary for natural
interactions. Our approach is to build and train 3D models of lip
motion to make up for the information we cannot always observe when
tracking. We use physical models as a prior and combine them with
statistical models, showing how the two can be smoothly and naturally
integrated into a synthesis method and a MAP estimation framework for
tracking. We have found that this approach allows us to accurately and
robustly track and synthesize the 3D shape of the lips from arbitrary
head poses in a 2D video stream. We demonstrate this with numerical
results on reconstruction accuracy, examples of static fits, and
audio-visual sequences. (C) 1998 Elsevier Science B.V. All rights
reserved.
|
299. | Aboul-Ella, H, Karam, H, and Nakajima, M, "Image metamorphosis transformation of facial images based on elastic body splines," SIGNAL PROCESSING, vol. 70, pp. 129-137, 1998.
Abstract:
In this paper, we propose a new image metamorphosis algorithm which
uses elastic body splines to generate warp functions for interpolating
scattered data points. The spline is based on a partial differential
equation proposed by Navier that describes the equilibrium displacement
of an elastic body subjected to forces. The spline maps can be
expressed as the linear combination of an affine transformation and a
Navier spline. The proposed algorithm generates a smooth warp that
reflects feature point correspondences. It is efficient in time
complexity and smoothly interpolated morphed images with only a
remarkably small number of specified feature points. The algorithm
allows each feature point in the source image to be mapped to the
corresponding feature point in the destination image. Once the images
are warped to align the positions of features and their shapes, the
in-between facial animation from two given facial images can be defined
by cross dissolving the positions of correspondence features and their
shapes and colors. We describe an efficient cross-dissolve algorithm
for generating the in-between images. (C) 1998 Published by Elsevier
Science B.V. All rights reserved.
|
300. | Chen, CW, Luo, JB, and Parker, KJ, "Image segmentation via adaptive K-mean clustering and knowledge-based morphological operations with biomedical applications," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 7, pp. 1673-1683, 1998.
Abstract:
Image segmentation remains one of the major challenges in image
analysis, since image analysis tasks are often constrained by how web
previous segmentation is accomplished. In particular, many existing
image segmentation algorithms fail to provide satisfactory results when
the boundaries of the desired objects are not clearly defined by the
image-intensity information. In medical applications, skilled operators
are usually employed to extract the desired regions that may be
anatomically separate but statistically indistinguishable. Such manual
processing is subject to operator errors and biases, is extremely time
consuming, and has poor reproducibility. We propose a robust algorithm
for the segmentation of three-dimensional (3-D) image data based on a
novel combination of adaptive K-mean clustering and knowledge-based
morphological operations. The proposed adaptive K-mean clustering
algorithm is capable of segmenting the regions of smoothly varying
intensity distributions. Spatial constraints are incorporated in the
clustering algorithm through the modeling of the regions by Gibbs
random fields, Knowledge-based morphological operations are then
applied to the segmented regions to identify the desired regions
according to the a priori anatomical knowledge of the
region-of-interest. This proposed technique has been successfully
applied to a sequence of cardiac CT volumetric images to generate the
volumes of left ventricle chambers at 16 consecutive temporal frames.
Our final segmentation results compare favorably with the results
obtained using manual outlining. Extensions of this approach to other
applications can be readily made when a priori knowledge of a given
object is available.
|
301. | Tsap, LV, Goldgof, DB, Sarkar, S, and Powers, PS, "A vision-based technique for objective assessment of burn scars," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 17, pp. 620-633, 1998.
Abstract:
In this paper a method for the objective assessment of burn scars is
proposed. The quantitative measures developed in this research provide
an objective way to calculate elastic properties of burn scars relative
to the surrounding areas, The approach combines range data and the
mechanics and motion dynamics of human tissues. Active contours are
employed to locate regions of interest and to find displacements of
feature points using automatically established correspondences, Changes
in strain distribution over time are evaluated, Given images at two
time instances and their corresponding features, the finite element
method Is used to synthesize strain distributions of the underlying
tissues, This results in a physically based framework for motion and
strain analysis. Relative elasticity of the burn scar is then recovered
using iterative descent search for the best nonlinear finite element
model that approximates stretching behavior of the region containing
the burn scar, The results from the skin elasticity experiments
illustrate the ability to objectively detect differences in elasticity
between normal and abnormal tissue, These estimated differences in
elasticity are correlated against the subjective judgments of
physicians that are presently the practice.
|
302. | Niessen, WJ, Romeny, BMT, and Viergever, MA, "Geodesic deformable models for medical image analysis," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 17, pp. 634-641, 1998.
Abstract:
In this paper implicit representations of deformable models for medical
image enhancement and segmentation are considered. The advantage of
implicit models over classical explicit models is that their topology
can he naturally adapted to objects in the scene, A geodesic
formulation of implicit deformable models is especially attractive
since it has the energy minimizing properties of classical models, The
aim of this pager is twofold, First, a modification to the customary
geodesic deformable model approach is introduced by considering all the
level sets in the image as energy minimizing contours. This approach is
used to segment multiple objects simultaneously and for enhancing and
segmenting cardiac computed tomography (CT) and magnetic resonance
images. Second, the approach is used to effectively compare implicit
and explicit models for specific tasks. This shows the complementary
character of implicit models since in case of poor contrast boundaries
or gaps in boundaries e.g. due to partial volume effects, noise, or
motion artifacts, they do not perform well, since the approach is
completely data-driven.
|
303. | Marescaux, J, Clement, JM, Tassetti, V, Koehl, C, Cotin, S, Russier, Y, Mutter, D, Delingette, H, and Ayache, N, "Virtual reality applied to hepatic surgery simulation: The next revolution," ANNALS OF SURGERY, vol. 228, pp. 627-634, 1998.
Abstract:
Objective
This article describes a preliminary work on virtual reality applied to
liver surgery and discusses the repercussions of assisted surgical
strategy and surgical simulation on tomorrow's surgery.
Summary Background Data
Liver surgery is considered difficult because of the complexity and
variability of the organ. Common generic tools for presurgical medical
image visualization do not fulfill the requirements for the liver,
restricting comprehension of a patient's specific liver anatomy.
Methods
Using data from the National Library of Medicine, a realistic
three-dimensional image was created, including the envelope and the
four internal arborescences. A computer interface was developed to
manipulate the organ and to define surgical resection planes according
to internal anatomy. The first step of surgical simulation was
implemented, providing the organ with real-time deformation computation.
Results
The three-dimensional anatomy of the liver could be clearly visualized.
The virtual organ could be manipulated and a resection defined
depending on the anatomic relations between the arborescences, the
tumor, and the external envelope. The resulting parts could also be
visualized and manipulated. The simulation allowed the deformation of a
liver model in real time by means of a realistic laparoscopic tool.
Conclusions
Three-dimensional visualization of the organ in relation to the
pathology is of great help to appreciate the complex anatomy of the
liver. Using virtual reality concepts (navigation, interaction, and
immersion), surgical planning, training, and teaching for this complex
surgical procedure may be possible. The ability to practice a given
gesture repeatedly will revolutionize surgical training, and the
combination of surgical planning and simulation will improve the
efficiency of intervention, leading to optimal care delivery.
|
304. | Tang, CK, and Medioni, G, "Inference of integrated surface, curve, and junction descriptions from sparse 3D data," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 20, pp. 1206-1223, 1998.
Abstract:
We are interested in descriptions of 3D data sets, as obtained from
stereo or a 3D digitizer. We therefore consider as input a sparse set
of points, possibly associated with certain orientation information. In
this paper, we address the problem of inferring integrated high-level
descriptions such as surfaces, So curves, and junctions from a sparse
point set. While the method proposed by Guy and Medioni provides
excellent results for smooth structures, it only detects surface
orientation discontinuities but does not localize them. For precise
localization, we propose a noniterative cooperative algorithm in which
surfaces, curves, and junctions work together: Initial estimates are
computed based on the work by Guy and Medioni, where each point in the
given sparse and possibly noisy point set is convolved with a
predefined vector mask to produce dense saliency maps. These maps serve
as input to our novel extremal surface and curve algorithms for initial
surface and curve extraction. These initial features are refined and
integrated by using excitatory and inhibitory fields. Consequently,
intersecting surfaces (resp. curves) are fused precisely at their
intersection curves (resp. junctions). Results on several synthetic as
well as real data sets are presented.
|
305. | Whitaker, RT, "A level-set approach to 3D reconstruction from range data," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 29, pp. 203-231, 1998.
Abstract:
This paper presents a method that uses the level sets of volumes to
reconstruct the shapes of 3D objects from range data. The strategy is
to formulate 3D reconstruction as a statistical problem: find that
surface which is mostly likely, given the data and some prior knowledge
about the application domain. The resulting optimization problem is
solved by an incremental process of deformation. We represent a
deformable surface as the level set of a discretely sampled scalar
function of three dimensions, i.e., a volume. Such level-set models
have been shown to mimic conventional deformable surface models by
encoding surface movements as changes in the greyscale values of the
volume. The result is a voxel-based modeling technology that offers
several advantages over conventional parametric models, including
flexible topology, no need for reparameterization, concise descriptions
of differential structure, and a natural scale space for hierarchical
representations. This paper builds on previous work in both 3D
reconstruction and level-set modeling. It presents a fundamental result
in surface estimation from range data: an analytical characterization
of the surface that maximizes the posterior probability. It also
presents a novel computational technique for level-set modeling, called
the sparse-field algorithm, which combines the advantages of a
level-set approach with the computational efficiency and accuracy of a
parametric representation. The sparse-field algorithm is more efficient
than other approaches, and because it assigns the level set to a
specific set of grid points, it positions the level-set model more
accurately than the grid itself. These properties, computational
efficiency and subcell accuracy, are essential when trying to
reconstruct the shapes of 3D objects. Results are shown for the
reconstruction objects from sets of noisy and overlapping range maps.
|
306. | Ong, KC, Teh, HC, and Tan, TS, "Resolving occlusion in image sequence made easy," VISUAL COMPUTER, vol. 14, pp. 153-165, 1998.
Abstract:
While the task of seamlessly merging computer-generated 3D objects into
an image sequence can be done manually, such effort often lacks
consistency across the images. It is also time consuming and prone to
error. This paper proposes a framework that solves the occlusion
problem without assuming a priori computer models from the input scene.
It includes a new algorithm to derive approximate 3D models about the
real scene based on recovered geometry information and user-supplied
segmentation results. The framework has been implemented, and it works
for amateur home videos. The result is an easy-to-use system for
applications like the visualization of new architectures in a real
environment.
|
307. | Ivins, J, and Porrill, J, "Constrained active region models for fast tracking in color image sequences," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 72, pp. 54-71, 1998.
Abstract:
Image segmentation is a fundamental problem in computer vision, for
which deformable models offer a partial solution. Most deformable
models work by performing some kind of edge detection; complementary
region growing methods have not often been used. As a result,
deformable models that track regions rather than edges have yet to be
developed to a great extent. Active region models are a relatively new
type of deformable model driven by a region energy that is a function
of the statistical characteristics of an image. This paper describes
the use of constrained active region models for frame-rate tracking in
color video images on widely available computer hardware. Two of the
many color representations now in use are reviewed for this purpose:
the intensity-based RGB space and the more intuitive HSV space.
Normalized RGB, which is essentially a measure of hue and saturation,
emerges as the preferred representation because it is invariant to
illumination changes and can be obtained from many frame-grabbers via a
simple fast software transformation. Three types of motion are examined
for constraining deformable models: rigid models can only translate and
rotate to fit image features; conformal models can also change size;
affine models exhibit two kinds of shearing in addition to the other
components. Two methods are described for producing affine motion,
given the desired unconstrained motion calculated by searching for
local energy minima lying perpendicular to the model boundary. An
existing method, based on iterative gradient descent, computes
translating, rotating, scaling, and shearing forces which can be
combined to produce affine and other types of motion. A faster, more
accurate method uses least-squares minimization to approximate the
desired motion; with this method it is also possible to derive specific
equations for rigid and conformal motion and to correct for the
aperture problem associated with the perpendicular search method. The
advantages of the new least-squares method are illustrated by using it
to drive an active region model via an affine transformation which
tracks the movements of a robot arm at frame rate in color video
images, (C) 1998 Academic Press.
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308. | Marescaux, J, Clementi, JM, Russier, Y, Tassetti, V, Mutter, D, Cotin, S, and Ayache, N, "A new concept in digestive surgery: the computer assisted surgical procedure, from virtual reality to telemanipulation.," ANNALES DE GASTROENTEROLOGIE ET D HEPATOLOGIE, vol. 34, pp. 126-131, 1998.
Abstract:
Surgical simulation increasingly appears to be an essential aspect of
tomorrow's surgery. The development of a hepatic surgery simulator is
an advanced concept calling for a new writing system which will
transform the medical world:virtual reality. Virtual reality extends
the perception of ourfive senses by representing more than the real
state of things by the means of computer sciences and robotics. it
consists of three concepts. immersion, navigation and interaction,
Three reasons have led us to develop this simulator: the first is to
provide the surgeon with a comprehensive visualisation of the organ.
The second reason is to allow for planning and surgical simulation that
could be compared with the detailed flight-plan for a commercial let
pilot. The third lies in the fact that virtual reality is an integrated
part of the concept of computer assisted surgical procedure. The
project consists bi a sophisticated simulator which has to includefive
requirements, visual fidelity, interactivity, physical properties,
physiological properties, sensory input and output. In this report we
will describe how to get a realistic 3D model of the liver from
bi-dimensional 2D medical images for anatomical and surgical training.
The introduction of a tumor and the consequent planning and virtual
resection is also described, as are force feedback and real-time
interaction.
|
309. | Bonciu, C, Leger, C, and Thiel, J, "A Fourier-Shannon approach to closed contours modelling," BIOIMAGING, vol. 6, pp. 111-125, 1998.
Abstract:
This paper describes a modelling method for continuous closed contours.
The initial input data set consists of two-dimensional (2-D) points,
which may be represented as a discrete function in a polar coordinate
system. The method uses the Shannon interpolation between these data
points to obtain the global continuous contour model. A minimal
description of the contour is obtained using the link between the
Shannon interpolation kernel and the Fourier series of polar
development (FSPD) for periodic functions. The Shannon interpolation
kernel allows the direct interpretation of the contour smoothness in
terms of both samples and Fourier frequency domains.
In order to deal with deformation point sources, often encountered in
active modelling techniques, a method of local deformation is proposed.
Each local deformation is performed in an angular sector centred on the
deformation point source. All the neighbouring characteristic samples
are displaced in order to minimize the oscillations of the newly
created model outside the deformation sector. This deformation
technique preserves the frequency characteristics of the contour,
regardless of the number and the intensity of deformation sources. In
this way, the technique induces a frequency modelling constraint, which
may be subsequently used in an active detection and modelling
environment.
Experiments on synthetic and real data prove the efficiency of the
proposed technique. The method is currently used to model contours of
the left ventricle of the heart obtained from ultrasound apical images.
This work is part of a larger project, the aim of which is to analyse
the space and time deformations of the left ventricle. The 2-D
Fourier-Shannon model is used as a basis for more complex
three-dimensional and four-dimensional Fourier models, able to recover
automatically the movement and deformation of the left ventricle of the
heart during a cardiac cycle.
|
310. | Wong, YY, Yuen, PC, and Tong, CS, "Segmented snake for contour detection," PATTERN RECOGNITION, vol. 31, pp. 1669-1679, 1998.
Abstract:
The active contour model, called snake, has been proved to be an
effective method in contour detection. This method has been
successfully employed in the areas of object recognition, computer
vision, computer graphics and biomedical images. However, this model
suffers from a great limitation, that is, it is difficult to locate
concave parts of an object. In view of such a limitation, a segmented
snake is designed and proposed in this paper. The basic idea of the
proposed method is to convert the global optimization of a closed snake
curve into local optimization on a number of open snake curves. The
segmented snake algorithm consists of two steps. In the first step, the
original snake model is adopted to locate the initial contour near the
object boundary. In the second step, a recursive split-and-merge
procedure is developed to determine the final object contour. The
proposed method is able to locate all convex, concave and high
curvature parts of an object accurately. A number of images are
selected to evaluate the capability of the proposed algorithm and the
results are encouraging. (C) 1998 Pattern Recognition Society.
Published by Elsevier Science Ltd. All rights reserved.
|
311. | Cunningham, GS, Hanson, KM, and Battle, XL, "Three-dimensional reconstructions from low-count SPECT data using deformable models," OPTICS EXPRESS, vol. 2, pp. 227-236, 1998.
Abstract:
We demonstrate the reconstruction of a 3D, time-varying bolus of
radiotracer from first-pass data obtained by the dynamic SPECT imager,
FASTSPECT, built by the University of Arizona. The object imaged is a
CardioWest Total Artificial Heart. The bolus is entirely contained in
one ventricle and its associated inlet and outlet tubes. The model for
the radiotracer distribution is a time-varying closed surface
parameterized by 162 vertices that are connected to make 960 triangles,
with uniform intensity of radiotracer inside. The total curvature of
the surface is minimized through the use of a weighted prior in the
Bayesian framework. MAP estimates for the vertices, interior intensity
and background count level are produced for diastolic and systolic
frames, the only two frames analyzed. The strength of the prior is
determined by finding the corner of the L-curve. The results indicate
that qualitatively pleasing results are possible even with as few as
1780 counts per time frame (total after summing over all 24 detectors).
Quantitative estimates of ejection fraction and wall motion should be
possible if certain restrictions in the model are removed, e.g., the
spatial homogeneity of the radiotracer intensity within the volume
defined by the triangulated surface, and smoothness of the surface at
the tube/ventricle join. (C) 1998 Optical Society of America.
|
312. | Ghanei, A, Soltanian-Zadeh, H, and Windham, JP, "A 3D deformable surface model for segmentation of objects from volumetric data in medical images," COMPUTERS IN BIOLOGY AND MEDICINE, vol. 28, pp. 239-253, 1998.
Abstract:
In this paper we present a new 3D discrete dynamic surface model. The
model consists of vertices and edges, which connect adjacent vertices.
Basic geometry of the model surface is generated by triangle patches.
The model deforms by internal and external forces. Internal forces are
obtained from local geometry of the model and are related to the local
curvature of the surface.;External forces, on the other hand, are based
on the image data and are calculated from desired image features. We
also present a method for generating an initial volume for the model
from a stack of initial contours, drawn by the user on cross sections
of the volumetric data. (C) 1998 Elsevier Science Ltd. All rights
reserved.
|
313. | Ghanei, A, Soltanian-Zadeh, H, and Windham, JP, "Segmentation of the hippocampus from brain MRI using deformable contours," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 22, pp. 203-216, 1998.
Abstract:
The application of a discrete dynamic contour model for segmentation of
the hippocampus from brain MRT has been investigated. Solutions to
several common problems of dynamic contours in this case and similar
cases have been developed. A new method for extracting the
discontinuous boundary of a structure with multiple edges near the
structure has been developed. The method is based on detecting and
following edges by external forces. The reliability of the final
contour and the model stability have been improved by using a
continuous mapping of the external energy and limiting movements of the
contour. The problem of optimizing the internal force weight has been
overcome by making it dependent on the amount of the external force.
Finally, the results of applying the proposed algorithm, which
implements the above modifications, to multiple applications have been
evaluated. (C) 1998 Elsevier Science Ltd. All rights reserved.
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314. | Mortensen, EN, and Barrett, WA, "Interactive segmentation with intelligent scissors," GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 60, pp. 349-384, 1998.
Abstract:
We present a new, interactive tool called Intelligent Scissors which we
use for image segmentation. Fully automated segmentation is an unsolved
problem, while manual tracing is inaccurate and laboriously
unacceptable. However, Intelligent Scissors allow objects within
digital images to be extracted quickly and accurately using simple
gesture motions with a mouse. When the gestured mouse position comes in
proximity to an object edge, a live-wire boundary "snaps" to, and wraps
around the object of interest. Live-wire boundary detection formulates
boundary detection as an optimal path search in a weighted graph.
Optimal graph searching provides mathematically piece-wise optimal
boundaries while greatly reducing sensitivity to local noise or other
intervening structures. Robustness is further enhanced with on-the-fly
training which causes the boundary to adhere to the specific type of
edge currently being followed, rather than simply the strongest edge in
the neighborhood. Boundary cooling automatically freezes unchanging
segments and automates input of additional seed points. Cooling also
allows the user to be much more free with the gesture path, thereby
increasing the efficiency and finesse with which boundaries can be
extracted. (C) 1998 Academic Press.
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315. | Siddiqi, K, Lauziere, YB, Tannenbaum, A, and Zucker, SW, "Area and length minimizing flows for shape segmentation," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 7, pp. 433-443, 1998.
Abstract:
A number of active contour models have been proposed that unify the
curve evolution framework with classical energy minimization techniques
for segmentation, such as snakes, The essential idea is to evolve a
curve (in two dimensions) or a surface (in three dimensions) under
constraints from image forces so that it clings to features of interest
in an intensity image, Recently, the evolution equation has been
derived from first principles as the gradient dow that minimizes a
modified length functional, tailored to features such as edges,
However, because the how may be slow to converge in practice, a
constant (hyperbolic) term is added to keep the curve/surface moving in
the desired direction, In this paper, we derive a modification of this
term based on the gradient how derived from a weighted area functional,
with image dependent weighting factor, When combined with the earlier
modified Length gradient dow, we obtain a partial differential equation
(PDE) that offers a number of advantages, as illustrated by several
examples of shape segmentation on medical images. In many cases the
weighted area how may be used on its own, with significant
computational savings.
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316. | Vilarino, DL, Brea, VM, Cabello, D, and Pardo, JM, "Discrete-time CNN for image segmentation by active contours," PATTERN RECOGNITION LETTERS, vol. 19, pp. 721-734, 1998.
Abstract:
In this work we present a new image segmentation strategy which
operates by means of active contours implemented on a multilayer
cellular neural network. The approach consists of an expanding and
thinning process, guided by external information from a contour which
evolves until it reaches the final desired position in the image
processed. (C) 1998 Elsevier Science B.V. All rights reserved.
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317. | Klemencic, A, Kovacic, S, and Pernus, F, "Automated segmentation of muscle fiber images using active contour models," CYTOMETRY, vol. 32, pp. 317-326, 1998.
Abstract:
The cross-sectional area of different fiber types is an important
anatomic feature in studying the structure and function of healthy and
diseased human skeletal muscles. However, such studies are hampered by
the thousands of fibers involved when manual segmentation has to be
used. We have developed a semiautomatic segmentation method that uses
computational geometry and recent computer vision techniques to
significantly reduce the time required to accurately segment the fibers
in a sample. The segmentation is achieved by simply pointing to the
approximate centroid of each fiber. The set of centroids is then used
to automatically construct the Voronoi polygons, which correspond to
individual fibers. Each Voronoi polygon represents the initial shape of
one active contour model, called a snake. In the energy minimization
process, which is executed in several stages, different external forces
and problem-specific knowledge are used to guide the snakes to converge
to fiber boundaries. Our results indicate that this approach for
segmenting muscle fiber images is fast, accurate, and reproducible
compared with manual segmentation performed by experts. Cytometry
32:317-326, 1998. (C) 1998 Wiley-Liss, Inc.
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318. | Basri, R, Costa, L, Geiger, D, and Jacobs, D, "Determining the similarity of deformable shapes," VISION RESEARCH, vol. 38, pp. 2365-2385, 1998.
Abstract:
Determining the similarity of two shapes is a significant task in both
machine and human vision systems that must recognize or classify
objects. The exact properties of human shape similarity judgements are
not well understood yet, and this task is particularly difficult in
domains where the shapes are not related by rigid transformations. In
this paper we identify a number of possibly desirable properties of a
shape similarity method, and determine the extent to which these
properties can be captured by approaches that compare local properties
of the contours of the shapes, through elastic matching. Special
attention is devoted to objects that possess articulations, i.e.
articulated parts. Elastic matching evaluates the similarity of two
shapes as the sum of local deformations needed to change one shape into
another. We show that similarities of part structure can be captured by
such an approach, without the explicit computation of part structure.
This may be of importance, since although parts appear to play a
significant role in visual recognition, it is difficult to stably
determine part structure. We also show novel results about how one can
evaluate smooth and polyhedral shapes with the same method. Finally, we
describe shape similarity effects that cannot be handled by current
approaches. (C) 1998 Elsevier Science Ltd. All rights reserved.
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319. | Tao, C, Li, RX, and Chapman, MA, "Automatic reconstruction of road centerlines from mobile mapping image sequences," PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, vol. 64, pp. 709-716, 1998.
Abstract:
An automatic approach to road centerline reconstruction from stereo
image sequences acquired by a mobile mapping system is introduced. The
road centerline reconstruction is treated as an inverse problem and
solved by global optimization techniques. The centerlines are described
by a physical curve model, which is composed of an abstract material
and deforms according to external and internal forces applied. The
external forces, generated from the centerline information extracted
from the image sequences, controls the local characteristics of the
model. The internal forces, arising from a priori knowledge of the road
shape, contribute to the global shape of the model. Unique constraints
that exist only in mobile mapping image sequences are utilized. The
developed system has been used for processing a large number of mobile
mapping image sequences. Road centerlines of the images under different
conditions have been reconstructed successfully. The research results
also make a contribution to the general field of structure from motion
and stereo.
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320. | Rougon, N, and Preteux, F, "Directional adaptive deformable models for segmentation," JOURNAL OF ELECTRONIC IMAGING, vol. 7, pp. 231-256, 1998.
Abstract:
We address the problem of adapting the functions controlling the
material properties of 2-D snakes, and show how introducing oriented
smoothness constraints results in a novel class of active contour
models for segmentation, which extends standard isotropic inhomogeneous
membrane/thin-plate stabilizers. These constraints, expressed as
adaptive L-2 matrix norms, are defined by two second-order symmetric
and positive definite tensors that are invariant with respect to rigid
motions in the image plane. These tensors, equivalent to directional
adaptive stretching and bending densities, are quadratic with respect
to first- and second-order derivatives of the image luminance,
respectively. A representation theorem specifying their canonical form
is established and a geometrical interpretation of their effects is
developed. Within this framework, it is shown that by achieving a
directional control of regularization such nonisotropic constraints
consistently relate the differential properties (metric and curvature)
of the deformable model with those of the underlying luminance surface,
yielding a satisfying preservation of image contour characteristics. In
particular, this model adapts to nonstationary curvature variations
along image contours to be segmented, thus providing a consistent
solution to curvature underestimation problems encountered near high
curvature contour points by classical snakes evolving with constant
material parameters. Optimization of the model within continuous and
discrete frameworks is discussed in detail. Finally, accuracy and
robustness of the model are established on synthetic images. Its
efficacy is further demonstrated on 2-D MRI sequences for which
comparisons with segmentations obtained using classical snakes are
provided. (C) 1998 SPIE and IS&T. [S1017-9909(98)02101-1].
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321. | Gold, S, Rangarajan, A, Lu, CP, Pappu, S, and Mjolsness, E, "New algorithms for 2D and 3D point matching: Pose estimation and correspondence," PATTERN RECOGNITION, vol. 31, pp. 1019-1031, 1998.
Abstract:
A fundamental open problem in computer vision-determining pose and
correspondence between two sets of points in space-is solved with a
novel, fast, robust and easily implementable algorithm. The technique
works on noisy 2D or 3D point sets that may be of unequal sizes and may
differ by non-rigid transformations. Using a combination of
optimization techniques such as deterministic annealing and the
softassign, which have recently emerged out of the recurrent neural
network/statistical physics framework, analog objective functions
describing the problems are minimized. Over thirty thousand
experiments, on randomly generated points sets with varying amounts of
noise and missing and spurious points, and on hand-written character
sets demonstrate the robustness of the algorithm. (C) 1998 Pattern
Recognition Society. Published by Elsevier Science Ltd. All rights
reserved.
|
322. | Li, ZP, "A neural model of contour integration in the primary visual cortex," NEURAL COMPUTATION, vol. 10, pp. 903-940, 1998.
Abstract:
Experimental observations suggest that contour integration may take
place in V1. However, there has yet to be a model of contour
integration that uses only known V1 elements, operations, and
connection patterns. This article introduces such a model, using
orientation selective cells, local cortical circuits, and horizontal
intracortical connections. The model is composed of recurrently
connected excitatory neurons and inhibitory interneurons, receiving
visual input via oriented receptive fields resembling those found in
primary visual cortex. Intracortical interactions modify initial
activity patterns from input, selectively amplifying the activities of
edges that form smooth contours in the image. The neural activities
produced by such interactions are oscillatory and edge segments within
a contour oscillate in synchrony. It is shown analytically and
empirically that the extent of contour enhancement and neural synchrony
increases with the smoothness, length, and closure of contours, as
observed in experiments on some of these phenomena. In addition, the
model incorporates a feedback mechanism that allows higher visual
centers selectively to enhance or suppress sensitivities to given
contours, effectively segmenting one from another. The model makes the
testable prediction that the horizontal cortical connections are more
likely to target excitatory (or inhibitory) cells when the two linked
cells have their preferred orientation aligned with (or orthogonal to)
their relative receptive field center displacements.
|
323. | Glasbey, CA, and Mardia, KV, "A review of image-warping methods," JOURNAL OF APPLIED STATISTICS, vol. 25, pp. 155-171, 1998.
Abstract:
Image warping is a transformation which maps all positions in one image
plane to positions in a second plane. It arises in many image analysis
problems, whether in order to remove optical distortions introduced by
a camera or a particular viewing perspective, to register art image
with a map or template, or to align two or more images. The choice of
warp is a compromise between a smooth distortion and one which achieves
a good match. Smoothness can be ensured by assuming a parametric form
for the warp or by constraining it using differential equations.
Matching can be specified by points to be brought into alignment, by
local measures of correlation between images, or by the coincidence of
edges. Parametric and non-parametric approaches to warping, and
matching criteria, are reviewed.
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324. | Gao, LM, Heath, DG, and Fishman, EK, "Abdominal image segmentation using three-dimensional deformable models," INVESTIGATIVE RADIOLOGY, vol. 33, pp. 348-355, 1998.
Abstract:
RATIONALE AND OBJECTIVES. The authors develop a three-dimensional (3-D)
deformable surface model-based segmentation scheme for abdominal
computed tomography (CT) image segmentation.
METHODS. A parameterized 3-D surface model was developed to represent
the human abdominal organs. An energy function defined on the direction
of the image gradient and the surface normal of the deformable model
was introduced to measure the match between the model and image data. A
conjugate gradient algorithm was adapted to the minimization of the
energy function.
RESULTS. Test results for synthetic images showed that the
incorporation of surface directional information improved the results
over those using only the magnitude of the image gradient. The
algorithm was tested on 21 CT datasets. Of the 21 cases tested, 11 were
evaluated visually by a radiologist and the results were judged to be
without noticeable error. The other 10 were evaluated over a distance
function. The average distance was less than 1 voxel.
CONCLUSIONS. The deformable model-based segmentation scheme produces
robust and acceptable outputs on abdominal CT images.
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325. | Xu, CY, and Prince, JL, "Snakes, shapes, and gradient vector flow," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 7, pp. 359-369, 1998.
Abstract:
Snakes, or active contours, are used extensively in computer vision and
image processing applications, particularly to locate object
boundaries, problems associated with initialization and poor
convergence to boundary concavities, however, have limited their
utility, This paper presents a new external force for active contours,
largely solving both problems. This external forte, which we call
gradient vector flow (GVF), is computed as a diffusion of the gradient
vectors of a gray-level or binary edge map derived from the image. It
differs fundamentally from traditional snake external forces in that it
cannot be written as the negative gradient of a potential function, and
the corresponding snake is formulated directly from a force balance
condition rather than a variational formulation. Using several
two-dimensional (2-D) examples and one three-dimensional (3-D) example,
we show that GVF has a large capture range and is able to move snakes
into boundary concavities.
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326. | Hager, GD, and Toyama, K, "X vision: A portable substrate for real-time vision applications," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 69, pp. 23-37, 1998.
Abstract:
In the past several years, the speed of standard processors has reached
the point where interesting problems requiring visual tracking can be
carried out on standard workstations. However, relatively little
attention has been devoted to developing visual tracking technology in
its own right. In this article, we describe X Vision, a modular,
portable framework for visual tracking. X Vision is designed to be a
programming environment for real-time vision which provides high
performance on standard workstations outfitted with a simple digitizer.
X Vision consists of a small set of image-level tracking primitives,
and a framework for combining tracking primitives to form complex
tracking systems. Efficiency and robustness are achieved by propagating
geometric and temporal constraints to the feature detection level,
where image warping and specialized image processing are combined to
perform feature detection quickly and robustly. Over the past several
years, we have used X Vision to construct several vision-based systems.
We present some of these applications as an illustration of how useful,
robust tracking systems can be constructed by simple combinations of a
few basic primitives combined with the appropriate task-specific
constraints. (C) 1998 Academic Press.
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327. | Piccioni, M, Scarlatti, S, and Trouve, A, "A variational problem arising from speech recognition," SIAM JOURNAL ON APPLIED MATHEMATICS, vol. 58, pp. 753-771, 1998.
Abstract:
By following the general approach of deformable templates, the problem
of recognizing a single word, independently of the speaker, is shown to
lead to the computation of the minimum value of some particular
functional. More precisely, this allows us to recover, for each
possible word in a prespecified set, the best matching with the
recorded signal; by selecting the minimum value, the recognition
problem can be solved. In this paper we are concerned with the detailed
study of the variational problem associated with this sort of
functional, namely, the existence of a minimum point and the features
of such a minimum. Finally, we discuss the convergence of a discretized
finite-dimensional approximation, suggested by the engineering
literature on this subject.
|
328. | Park, JS, and Han, JH, "Contour matching: a curvature-based approach," IMAGE AND VISION COMPUTING, vol. 16, pp. 181-189, 1998.
Abstract:
The lack of information about tangential velocity makes velocity
estimation erroneous in contour matching. Classical methods use the
normal velocity, together with some smoothness constraints, since the
tangential velocity cannot be recovered. This paper presents a contour
matching method that computes displacements with a criteria of minimum
curvature differences. The first derivative of tangential velocity is
available from the image intensities and is related to the contour
curvature. We compute the velocities using the curvature as well as the
normal component. Consequently, the estimation error due to the
tangential component is reduced substantially. A contour having
occluding parts leads to mismatching. Our method determines occluding
parts before the contour matching by analyzing the change of curvature
distribution. Experimental results showed that the proposed method
computes accurate velocity vectors for various moving contours. (C)
1998 Elsevier Science B.V.
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329. | Chandran, S, and Potty, AK, "Energy minimization of contours using boundary conditions," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 20, pp. 546-549, 1998.
Abstract:
Reconstruction of objects from a scene may be viewed as a data fitting
problem using energy minimizing splines as the basic shape. The process
of obtaining the minimum to construct the "best" shape can sometimes be
important. Some of the potential problems in the Euler-Lagrangian
variational solution proposed in the original formulation [1], were
brought to light in [2], and a dynamic programming (DP) method was also
suggested. In this paper we further develop the DP solution. We show
that in certain cases, the discrete form of the solution in [2], and
adopted subsequently [3], [4], [5], [6] may also produce local minima,
and develop a strategy to avoid this. We provide a stronger form of the
conditions necessary to derive a solution when the energy depends on
the second derivative, as in the case of "active contours.".
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330. | Sakalli, M, and Yan, H, "Feature-based compression of human face images," OPTICAL ENGINEERING, vol. 37, pp. 1520-1529, 1998.
Abstract:
A method is developed for feature-based coding of human face images.
Deformable templates, wavelet decomposition, and residual vector
quantization (RVQ) form three consecutive stages of the proposed
method, which aims for recognition-based very low bit rate coding.
Deformable templates are employed in localization of facial features
and biorthogonal spline filters are used for the decomposition of
segmented and normalized face images. Wavelet coefficients are zonal
truncated before being vector quantized to generate multiresolution
codebooks. Classified multiresolution codebooks are also generated for
residual eye and mouth images to improve subjective quality of salient
face features. (C) 1998 Society of Photo-Optical Instrumentation
Engineers. [S0091-3286(98)02105-9].
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331. | Lefebvre, F, Berger, G, and Laugier, P, "Automatic detection of the boundary of the calcaneus from ultrasound parametric images using an active contour model; Clinical assessment," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 17, pp. 45-52, 1998.
Abstract:
This paper presents a computerized method for automated detection of
the boundary of the os calcis on in vivo ultrasound parametric images,
using an active dynamic contour model. The initial contour, defined
without user interaction, is an iso-contour extracted from the textural
feature space. The contour is deformed through the action of internal
and external forces, until stability is reached. The external forces,
which characterize image features, are a combination of gray-level
information and second-order textural features arising from local
cooccurrence matrices. The broadband ultrasound attenuation (BUA) value
is then averaged within the contour obtained.
The method was applied to 381 clinical images. The contour was
correctly detected in the great majority of the cases, For the
short-term reproducibility study, the mean coefficient of variation was
equal to 1.81% for BUA values and 4.95% for areas in the detected
region. Women with osteoporosis had a lower BUA than age-matched
controls (p = 0.0005). In healthy women, the age-related decline was
-0.45 dB/MHz/yr. In the group of healthy post-menopausal women, years
since menopause, weight and age were significant predictors of BUA,
These results are comparable to those obtained when averaging BUA
values in a small region of interest.
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332. | Atkins, MS, and Mackiewich, BT, "Fully automatic segmentation of the brain in MRI," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 17, pp. 98-107, 1998.
Abstract:
A robust fully automatic method for segmenting the brain from head
magnetic resonance (MR) images has been developed, which works even in
the presence of radio frequency (RF) inhomogeneities. It has been
successful in segmenting the brain in every slice from head images
acquired from several different MRI scanners, using
different-resolution images and different echo sequences.
The method uses an integrated approach which employs image processing
techniques based on anisotropic filters and "snakes" contouring
techniques, and a priori knowledge, which is used to remove the eyes,
which are tricky to remove based on image intensity alone, It is a
multistage process, involving first removal of the background noise
leaving a head mask, then finding a rough outline of the brain, then
refinement of the rough brain outline to a final mask.
The paper describes the main features of the method, and gives results
for some brain studies.
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333. | Tong, AWK, Qureshi, R, Li, X, and Sather, AP, "A system for ultrasound image segmentation for loin eye measurements in swine," CANADIAN AGRICULTURAL ENGINEERING, vol. 40, pp. 47-53, 1998.
Abstract:
An image segmentation system was developed for detecting the muscle
longissimus thoraces (LT) in ultrasonic images of live pigs. The images
have a low contrast, a high level of noise, and a high degree of
variance in terms of texture and shape. The segmentation algorithm
starts with a region growing process, which provides a rough
approximation of the LT. Morphological operations and curve fitting
eliminate unwanted noise. Finally, an active contour process refines
the shape of the resulting region. This system takes several
segmentation techniques and builds a flow of information between them
but does not rely on specific a priori information of the texture or
the contrast. This is a first step towards automating the loin
detection in ultrasonic images of live pigs. initial experiments
provided encouraging results. It is a modular system so that different
region growing and refinement algorithms can be easily substituted into
the current design. This makes for a general system that can be adapted
to other segmentation tasks involving low contrast images. A series of
three ultrasound images was made along the dorsal surface of 30 live
pigs. Using the images to estimate loin volume, 64 and 70% of the
variation in commercial loin weight and lean yield of loin were
predicted. Augmenting the model with backfat measurements, the R-2
increased to 79 and 89%, respectively. These values compare to 76 and
79%, respectively, from measurements made on the carcass with the
Hennessey Grading Probe.
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334. | Thalmann, NM, Kalra, P, and Escher, M, "Face to virtual face," PROCEEDINGS OF THE IEEE, vol. 86, pp. 870-883, 1998.
Abstract:
The first virtual humans appeared in the early 1980's in such films as
Dreamflight (1982) and The Juggler (1982). Pioneering work in the
ensuing period focused on realistic appearance in the simulation of
virtual humans. In the 1990's, the emphasis has shifted to real-time
animation and interaction in virtual worlds. Virtual humans halle begun
to inhabit virtual worlds and so have we. To prepare our place in the
virtual world, we first develop techniques for the automatic
representation of a human face capable of being animated in real time
using both video and audio input. The objective is for one's
representative to look, talk, and behave like oneself in the virtual
world. Furthermore, the virtual inhabitants of this world should be
able to see our avatars and to react to what we say and to the emotions
we convey.
This paper sketches an overview of the problems related to the analysis
and synthesis of face-to-virtual-face communication in a virtual world.
We describe different components of our system for real-time
interaction and communication between a cloned face representing a real
person and an autonomous virtual face. It provides an insight into the
various problems and gives particular solutions adopted in
reconstructing a virtual clone capable of reproducing the shape and
movements of the real person's face. It includes the analysis of the
facial expression and speech of the cloned face, which can be used to
elicit a response from the autonomous virtual human with both verbal
and nonverbal facial movements synchronized with the audio voice.
We believe that such a system can be exploited in many applications
such as natural and intelligent human-machine interfaces, virtual
collaboration work, virtual learning and teaching, and so on.
|
335. | Memin, E, and Perez, P, "Dense estimation and object-based segmentation of the optical flow with robust techniques," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 7, pp. 703-719, 1998.
Abstract:
In this paper, we address the issue of recovering and segmenting the
apparent velocity field in sequences of images. As for motion
estimation, we minimize an objective function involving two robust
terms. The first one cautiously captures the optical flow constraint,
while the second (a priori) term incorporates a
discontinuity-preserving smoothness constraint. To cope with the
nonconvex minimization problem thus defined, we design an efficient
deterministic multigrid procedure. It converges fast toward estimates
of good quality, while revealing the large discontinuity structures of
flow fields. We then propose an extension of the model by attaching to
it a flexible object-based segmentation device based on deformable
closed curves (different families of curve equipped with different
kinds of prior can be easily supported). Experimental results on
synthetic and natural sequences are presented, including an analysis of
sensitivity to parameter tuning.
|
336. | Steiner, A, Kimmel, R, and Bruckstein, AM, "Planar shape enhancement and exaggeration," GRAPHICAL MODELS AND IMAGE PROCESSING, vol. 60, pp. 112-124, 1998.
Abstract:
A local smoothing operator applied in the reverse direction is used to
obtain planar shape enhancement and exaggeration. Inversion of a
smoothing operator is an inherently unstable operation. Therefore, a
stable numerical scheme simulating the inverse smoothing effect is
introduced. Enhancement is obtained for short time spans of evolution.
Carrying the evolution further yields shape exaggeration or
caricaturization effect. Introducing attraction forces between the
evolving shape and the initial one yields an enhancement process that
converges to a steady state. These forces depend on the distance of the
evolving curve from the original one and on local properties. Results
of applying the unrestrained and restrained evolution on planar shapes,
based on a stabilized inverse geometric heat equation, are presented
showing enhancement and caricaturization effects. (C) 1998 Academic
Press.
|
337. | Tsap, LV, Goldgof, DB, Sarkar, S, and Huang, WC, "Efficient nonlinear finite element modeling of nonrigid objects via optimization of mesh models," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 69, pp. 330-350, 1998.
Abstract:
In this paper we propose a new general framework for the application of
the nonlinear finite element method (FEM) to nonrigid motion analysis,
We construct the models by integrating image data and prior knowledge,
using well-established techniques from computer vision, structural
mechanics, and computer-aided design (CAD). These techniques guide the
process of optimization of mesh models.
Linear FEM proved to be a successful physically based modeling tool in
solving limited types of nonrigid motion problems, However, linear FEM
cannot handle nonlinear materials or large deformations. Application of
nonlinear FEM to nonrigid motion analysis has been restricted by
difficulties with high computational complexity and noise sensitivity.
We tackle the problems associated with nonlinear FEM by changing the
parametric description of the object to allow easy automatic control of
the model, using physically motivated analysis of the possible
displacements to address the worst effects of the noise, applying mesh
control strategies, and utilizing multiscale methods. The combination
of these methods represents a new systematic approach to a class of
nonrigid motion applications for which sufficiently precise and
flexible FEM models can be built,
The results from the skin elasticity experiments demonstrate the
success of the proposed method. The model allows us to objectively
detect the differences in elasticity between normal and abnormal skin,
Our work, demonstrates the possibility of accurate computation of point
correspondences and force recovery from range image sequences
containing nonrigid objects and large motion. (C) 1998 Academic Press.
|
338. | Wong, YY, Yuen, PC, and Tong, CS, "Contour length terminating criterion for snake model," PATTERN RECOGNITION, vol. 31, pp. 597-606, 1998.
Abstract:
The snake model, that involves a recursive scheme for contour
searching, is widely employed in object contour detection. In a
recursive algorithm, a terminating criterion is essential to terminate
the process. However, existing terminating criteria for snake cannot
acquire good results for contour detection. Two commonly employed
terminating criteria for snake are addressed and their limitations on
stability and reliability are discussed. A novel terminating criterion,
named as contour length criterion (CL-criterion), is developed and
reported in this paper. This criterion measures the normalized total
length of the contour at each iteration. A number of images are
selected to evaluate the effect of applying the proposed terminating
criterion on the snake model and the results are encouraging. Compared
to existing criteria, the proposed method is more stable and reliable.
(C) 1998 Pattern Recognition Society. Published by Elsevier Science
Ltd. All rights reserved.
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1999 |
339. | Hassanien, AE, and Nakajima, M, "Feature-specification algorithm based on snake model for facial image morphing," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E82D, pp. 439-446, 1999.
Abstract:
In this paper a new snake model for image morphing with semiautomated
delineation which depends on Hermite's interpolation theory, is
presented. The snake model will be used to specify the correspondence
between features in two given images. It allows a user to extract a
contour that defines a facial feature such as the lips, mouth, and
profile, by only specifying the endpoints of the contour around the
feature which we wish to define. We assume that the user can specify
the endpoints of a curve around the features that serve as the
extremities of a contour. The proposed method automatically computes
the image information around these endpoints which provides the
boundary conditions. Then the contour is optimized by taking this
information into account near its extremities. During the iterative
optimization process, the image forces are turned on progressively from
the contour extremities toward the center to define the exact position
of the feature. The proposed algorithm helps the user to easily define
the exact position of a feature. It may also reduce the time required
to establish the features of an image.
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340. | Peterfreund, N, "The velocity snake: Deformable contour for tracking in spatio-velocity space," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 73, pp. 346-356, 1999.
Abstract:
We present a new active contour model for boundary tracking and
position prediction of nonrigid objects, which results from applying a
velocity control to the class of elastodynamical contour models, known
as snakes, The proposed control term minimizes an energy dissipation
function which measures the difference between the contour velocity and
the apparent velocity of the image. Treating the image video-sequence
as continuous measurements along time, it is shown that the proposed
control results in robust tracking. This is in contrast to the original
snake model which is proven to have tracking errors relative to image
(object) velocity, thus resulting in high sensitivity to image clutter.
The motion estimation further allows for position prediction of
nonrigid boundaries. Based on the proposed central approach, we propose
a new class of real time tracking contours, varying from models with
batch-mode control estimation to models with real time adaptive
controllers. (C) 1999 Academic Press.
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341. | Astrom, K, and Kahl, F, "Motion estimation in image sequences using the deformation of apparent contours," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 21, pp. 114-127, 1999.
Abstract:
The problem of determining the camera motion from apparent contours or
silhouettes of a priori unknown curved three-dimensional surfaces is
considered. In a sequence of images, it is shown how to use the
generalized epipolar constraint an apparent contours. One such
constraint is obtained for each epipolar tangency point in each image
pair. An accurate algorithm for computing the motion is presented based
on a maximum likelihood estimate. It is shown how to generate initial
estimates on the camera motion using only the tracked contours. It is
also shown that in theory the motion can be calculated from the
deformation of a single contour. The algorithm has been tested on
several real image sequences, for both Euclidean and protective
reconstruction. The resulting motion estimate is compared to motion
estimates calculated independently using standard feature-based
methods. The motion estimate is also used to classify the silhouettes
as curves or apparent contours. This is a strong indication that the
motion estimate is of good quality. The statistical evaluation shows
that the technique gives accurate and stable results.
|
342. | Gabrani, M, and Tretiak, OJ, "Surface-based matching using elastic transformations," PATTERN RECOGNITION, vol. 32, pp. 87-97, 1999.
Abstract:
We introduce a methodology for the alignment of multidimensional data,
such as brain scans. The proposed approach does not require
fiducial-point correspondence; correspondence of surfaces provides
sufficient data for registration. We extend multidimensional
interpolation theory by using a more general form of energy functional,
which leads to basis functions that have different orders at zero and
infinity. This allows flexibility in the design of the interpolation
solution. The problem is transformed into a linear algebra problem. Two
techniques for better conditioning of the system matrix are described.
Experimental results on two- and three-dimensional alignment of brain
data used in neurochemistry research are shown. (C) 1999 Pattern
Recognition Society. Published by Elsevier Science Ltd. All rights
reserved.
|
343. | Denney, TS, "Estimation and detection of myocardial tags in MR image without user-defined myocardial contours," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 330-344, 1999.
Abstract:
Magnetic resonance (MR) tagging has been Shown to, be a useful
technique for noninvasively measuring the deformation of an in vivo
heart. An important step in analyzing tagged images is the
identification of tag lines in each image of a cine sequence. Most
existing tag identification algorithms require user defined myocardial
contours. Contour identification, however, is time consuming and
requires a considerable amount of user intervention. In this paper, a
new method for identifying tag lines, which me call the ML/MAP method,
is presented that does not require user defined myocardial contours.
The ML/MAP method is composed of three stages. First, a set of
candidate tag line centers is estimated across the entire
region-of-interest (ROI) with a snake algorithm based on a
maximum-likelihood (ML) estimate of the tag center. Next, a maximum a
posteriori (MAP) hypothesis test is used to detect the candidate tag
centers that are actually part of a tag line. Finally, a pruning
algorithm is used to remove any detected tag line centers that do not
meet a spatio-temporal continuity criterion. The ML/MAP method is
demonstrated on data from ten in vivo human hearts.
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344. | Gu, YH, and Tjahjadi, T, "Efficient planar object tracking and parameter estimation using compactly represented cubic B-Spline curves," IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, vol. 29, pp. 358-367, 1999.
Abstract:
In this paper, we consider the problem of matching tno-dimensional
(2-D) planar object curves from a database, and tracking moving object
curves through an image sequence, The first part of the paper describes
a curve data compression method using B-spline curve approximation. We
present a new constrained active B-spline curie model based on the
minimum mean square error (MMSE) criterion, and an iterative algorithm
for selecting the "best" segment border points for each B-spline curve,
The second part of the paper describes a method for simultaneous object
tracking and affine parameter estimation using the approximate curves
and profiles, We propose a novel B-spline point assignment algorithm
which incorporates the significant corners for interpolating
corresponding paints on the two curves to be compared. A gradient-based
algorithm is presented for simultaneously tracking object curl es, and
estimating the associated translation, rotation and scaling parameters.
The performance of each proposed method is evaluated using still images
and image sequences containing simple objects.
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345. | Kang, DJ, "A fast and stable snake algorithm for medical images," PATTERN RECOGNITION LETTERS, vol. 20, pp. 507-512, 1999.
Abstract:
A discrete dynamic model for defining and tracking contours in 2-D
medical images is presented. An active contour in this objective is
optimized by a dynamic programming algorithm, for which a new
constraint that has fast and stable properties is introduced. The
internal energy of the model depends on local behavior of the contour,
while the external energy is derived from image features. The algorithm
is able to rapidly detect convex and concave objects even when the
image quality is poor. (C) 1999 Elsevier Science B.V. All rights
reserved.
|
346. | Zhu, Y, Chen, JX, Xiao, S, and Mac Mahon, EB, "3D knee modeling and biomechanical simulation," COMPUTING IN SCIENCE & ENGINEERING, vol. 1, pp. 82-87, 1999.
Abstract:
This paper considers the problem of generating various calligraphy from
some sample fonts. Our method is based on the deformable contour model
g-snake. By representing the outline of each stroke of a character with
a g-snake, we cast the generation problem into global and local
deformation of g-snake under different control parameters, where the
local deformation obeys the energy minimization principle of
regularization technique. The base values of the control parameters are
learned from given sample fonts. The experimental results on alphabet
and Japanese characters Hiragana show such processing as a reasonable
method for generating calligraphy.
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347. | Wang, LS, He, LF, Nakamura, T, Mutoh, A, and Itoh, H, "Calligraphy generation using deformable contours," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E82D, pp. 1066-1073, 1999.
Abstract:
This paper considers the problem of generating various calligraphy from
some sample fonts. Our method is based on the deformable contour model
g-snake. By representing the outline of each stroke of a character with
a g-snake, we cast the generation problem into global and local
deformation of g-snake under different control parameters, where the
local deformation obeys the energy minimization principle of
regularization technique. The base values of the control parameters are
learned from given sample fonts. The experimental results on alphabet
and Japanese characters Hiragana show such processing as a reasonable
method for generating calligraphy.
|
348. | Hu, JM, Yan, H, and Sakalli, M, "Locating head and face boundaries for head-shoulder images," PATTERN RECOGNITION, vol. 32, pp. 1317-1333, 1999.
Abstract:
This paper presents a model-based approach to locate head and face
boundaries in a head-shoulder image with plain background. Three models
are constructed for the images, where the head boundary is divided into
left/right sub-boundaries and the face boundary is divided into
left/right and top/bottom sub-boundaries. The left/right head
boundaries are located from two thresholded images and the final result
is the combination of them. After the head boundary is located, the
four face sub-boundaries are located from the grey edge image. The
algorithm is carried out iteratively by detecting low-level edges and
then organizing/verifying them using high-level knowledge of the
general shape of a head. The experimental results using a database of
300 images show that this approach is promising. (C) 1999 Pattern
Recognition Society. Published by Elsevier Science Ltd. All rights
reserved.
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349. | Baumgartner, A, Steger, C, Mayer, H, Eckstein, W, and Ebner, H, "Automatic road extraction based on multi-scale, grouping, and context," PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, vol. 65, pp. 777-785, 1999.
Abstract:
An approach for the automatic extraction of roads from digital aerial
imagery is proposed. It makes use of several versions of the same
aerial image with different resolutions. Roads are modeled as a network
of intersections and links between these intersections, and are found
by a grouping process. The context of roads is hierarchically
structured into a global and a local level. The automatic segmentation
of the aerial image into different global contexts, i.e., rural,
forest, and urban area, is used to focus the extraction to the most
promising regions. For the actual extraction of the roads, edges are
extracted in the original high resolution image (0.2 to 0.5 m) and
lines are extracted in an image of reduced resolution. Using both
resolution levels and explicit knowledge about roads, hypotheses for
road segments are generated. They are grouped iteratively into larger
segments. in addition to the grouping algorithms, knowledge about the
local context, e.g., shadows cast by a tree onto a road segment, is
used to bridge gaps. To construct the road network, finally
intersections are extracted. Examples and results of an evaluation
based on manually plotted reference data are given, indicating the
potential of the approach.
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350. | Kang, DJ, "Stable snake algorithm for convex tracking of MRI sequences," ELECTRONICS LETTERS, vol. 35, pp. 1070-1071, 1999.
Abstract:
A snake model for convex tracking contours in 2D medical images is
presented. By modelling the local behaviour of the contour, a new
constraint that has fast and stable properties is obtained with
optimisation by a dynamic programming algorithm.
|
351. | Mardia, KV, Walder, AN, Berry, E, Sharples, D, Millner, PA, and Dickson, RA, "Assessing spinal shape," JOURNAL OF APPLIED STATISTICS, vol. 26, pp. 735-745, 1999.
Abstract:
Idiopathic scoliosis is the most common spinal deformity, affecting
perhaps as many as 5% of children. Early recognition of the condition
is essential for optimal treatment. A widely used technique for
identification is based on a somewhat crude angle measurement from a
frontal spinal X-ray. Here, we provide a technique and new summary
statistical measures for classifying spinal shape, and present results
obtained from clinical X-rays.
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352. | Sinthanayothin, C, Boyce, JF, Cook, HL, and Williamson, TH, "Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images," BRITISH JOURNAL OF OPHTHALMOLOGY, vol. 83, pp. 902-910, 1999.
Abstract:
Aim-To recognise automatically the main components of the fundus on
digital colour images.
Methods-The main features of a fundus retinal image were defined as the
optic disc, fovea, and blood vessels. Methods are described for their
automatic recognition and location. 112 retinal images were
preprocessed via adaptive, local, contrast enhancement. The optic discs
were located by identifying the area with the highest variation in
intensity of adjacent pixels. Blood vessels were identified by means of
a multilayer perceptron neural net, for which the inputs were derived
from a principal component analysis (PCA) of the image and edge
detection of the first component of PCA. The foveas were identified
using matching correlation together with characteristics typical of a
fovea-for example, darkest area in the neighbourhood of the optic disc.
The main components of the image were identified by an experienced
ophthalmologist for comparison with computerised methods.
Results-The sensitivity and specificity of the recognition of each
retinal main component was as follows: 99.1% and 99.1% for the optic
disc; 83.3% and 91.0% for blood vessels; 80.4% and 99.1% for the fovea.
Conclusions-In this study the optic disc, blood vessels, and fovea were
accurately detected. The identification of the normal components of the
retinal image will aid the future detection of diseases in these
regions. In diabetic retinopathy, for example, an image could be
analysed for retinopathy with reference to sight threatening
complications such as disc neovascularisation, vascular changes, or
foveal exudation.
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353. | Zhao, BS, Reeves, AP, Yankelevitz, DF, and Henschke, CI, "Three-dimensional multicriterion automatic segmentation of pulmonary nodules of helical computed tomography images," OPTICAL ENGINEERING, vol. 38, pp. 1340-1347, 1999.
Abstract:
A 3-D multicriterion automatic segmentation algorithm is developed to
improve accuracy of delineation of pulmonary nodules on helical
computed tomography (CT) images by removing their adjacent structures.
The algorithm applies multiple gray-value thresholds to a nodule region
of interest (ROI). At each threshold level, the nodule candidate in the
ROI is automatically detected by labeling 3-D connected components,
followed by a 3-D morphologic opening operation. Once the nodule
candidate is found, its two specific parameters, gradient strength of
the nodule surface and a 3-D shape compactness factor, can be computed.
The optimal threshold can be determined by analyzing these parameters.
Our experiments with in vivo nodules demonstrate the feasibility of
employing this algorithm to improve the accuracy of nodule delineation,
especially for small nodules less than 1 cm in diameter. This discloses
the potential of the algorithm for accurate characterizations of
nodules (e.g., volume, change in volume over time) at an early stage,
which can help to provide valuable guidance for further clinical
management. (C) 1999 Society of Photo-Optical Instrumentation Engineers.
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354. | Stammberger, T, Eckstein, F, Michaelis, M, Englmeier, KH, and Reiser, M, "Interobserver reproducibility of quantitative cartilage measurements: Comparison of B-spline snakes and manual segmentation," MAGNETIC RESONANCE IMAGING, vol. 17, pp. 1033-1042, 1999.
Abstract:
The objective of this work was to develop a segmentation technique for
thickness measurements of the articular cartilage in MR images and to
assess the interobserver reproducibility of the method in comparison
with manual segmentation. The algorithm is based on a B-spline snakes
approach and is able to delineate the cartilage boundaries in real time
and with minimal user interaction. The interobserver reproducibility of
the method, ranging from 3.3 to 13.6% for various section orientations
and joint surfaces, proved to be significantly superior to manual
segmentation. (C) 1999 Elsevier Science Inc.
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355. | Shyu, CR, Brodley, CE, Kak, AC, Kosaka, A, Aisen, AM, and Broderick, LS, "ASSERT: A physician-in-the-loop content-based retrieval system for HRCT image databases," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 75, pp. 111-132, 1999.
Abstract:
It is now recognized in many domains that content-based image retrieval
from a database of images cannot be carried out by using completely
automated approaches. One such domain is medical radiology for which
the clinically useful information in an image typically consists of
gray level variations in highly localized regions of the image.
Currently, it is not possible to extract these regions by automatic
image segmentation techniques. To address this problem, we have
implemented a human-in-the-loop (a physician-in-the-loop, more
specifically) approach in which the human delineates the pathology
bearing regions (PBR) and a set of anatomical landmarks in the image
when the image is entered into the database. To the regions thus
marked, our approach applies low-level computer vision and image
processing algorithms to extract attributes related to the variations
in gray scale, texture, shape, etc. In addition, the system records
attributes that capture relational information such as the position of
a PER with respect to certain anatomical landmarks. An overall
multidimensional index is assigned to each image based on these
attribute values. (C) 1999 Academic Press.
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356. | Koss, JE, Newman, FD, Johnson, TK, and Kirch, DL, "Abdominal organ segmentation using texture transforms and a Hopfield neural network," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 640-648, 1999.
Abstract:
Abdominal organ segmentation is highly desirable but difficult, due to
large differences between patients and to overlapping grey-scale values
of the various tissue types. The first step in automating this process
is to cluster together the pixels within each organ or tissue type. We
propose to Form images based on second-order statistical texture
transforms (Haralick transforms) of a CT or MRI scan. The original scan
plus the suite of texture transforms are then input into a Hopfield
neural network (HNN). The network is constructed to solve an
optimization problem, where the best solution is the minima of a
Lyapunov energy function. On a sample abdominal CT scan, this process
successfully clustered 79-100% of the pixels of seven abdominal organs.
It is envisioned that this Is the first step to automate segmentation.
Active contouring (e.g., SNAKE's) or a back-propagation neural network
can then be used to assign names to the clusters and fill in the
incorrectly clustered pixels.
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357. | Chang, MW, Lin, E, and Hwang, JN, "Contour tracking using a knowledge-based snake algorithm to construct three-dimensional pharyngeal bolus movement," DYSPHAGIA, vol. 14, pp. 219-227, 1999.
Abstract:
Videofluorography (VFG) using a barium-mixed bolus is in wide clinical
use for assessing patients with swallowing disorders. VFG is usually
done with both lateral (LA) and anterior-posterior (AP) views, most
commonly in two separate sittings. A real-time, three-dimensional (3-D)
representation of the evolution of a pharyngeal bolus and its
volumetric information can potentially help clinicians analyze and
visualize the kinematics of swallowing, dysphagia, and compensatory
therapeutic strategies. Active contour models, also known as "Snakes,"
have been used to solve various image analysis and computer vision
problems. We applied a Snake algorithm to automate in part the contour
tracking and reconstruction of VFG images to visualize and
quantitatively analyze the 3-D evolution of a pharyngeal bolus. To
improve the accuracy of the Snake search, we provided the additional
"knowledge" of the pharyngeal image itself, which served as an extra
constraint to push the Snake curve toward the desired contour. VFG of
pharyngeal bolus transport in a normal subject was recorded by using
barium-mixed boluses (viscosity: 185 centipoise, density: 2.84 g/cc)
with volumes of 5, 10, and 20 ml, The resulting LA and AP video images
were digitally captured and matched frame by frame. The knowledge-based
Snake search algorithm was used to generate Snake points to satisfy
both internal (i.e., smoothness) and external (i.e., boundary fitting)
constraints. Using these Snake points, we traced the 3-D bolus movement
at each time instant, assuming elliptic geometry in the cross-section
of the pharyngeal bolus. By concatenating the 3-D images for each time
instant, we developed a 3-D movie representing pharyngeal bolus
movement. The efficiency, reproducibility, and accuracy of this
algorithm in tracing pharyngeal bolus boundaries and estimating
front/tail velocities were assessed and found satisfactory. We conclude
that 3-D pharyngeal bolus movement can be traced both accurately and
efficiently by using a knowledge-based Snake search algorithm.
|
358. | Kobbelt, LP, Vorsatz, J, Labsik, U, and Seidel, HP, "A shrink wrapping approach to remeshing polygonal surfaces," COMPUTER GRAPHICS FORUM, vol. 18, pp. C119-+, 1999.
Abstract:
Due to their simplicity and flexibility, polygonal meshes are about to
become the standard representation for surface geometry in computer
graphics applications. Some algorithms in the context of
multiresolution representation and modeling can be performed much more
efficiently and robustly if the underlying surface tesselations have
the special subdivision connectivity In this paper we propose a new
algorithm for converting a given unstructured triangle mesh into one
having subdivision connectivity. The basic idea is to simulate the
shrink wrapping process by adapting the deformable surface technique
known from image processing. The resulting algorithm generates
subdivision connectivity meshes whose base meshes only have a very
small number of triangles. The iterative optimization process that
distributes the mesh vertices over the given surface geometry
guarantees low local distortion of the triangular faces. We show
several examples and applications including the progressive
transmission of subdivision surfaces.
|
359. | Bhandarkar, SM, and Zeng, X, "Evolutionary approaches to figure-ground separation," APPLIED INTELLIGENCE, vol. 11, pp. 187-212, 1999.
Abstract:
The problem of figure-ground separation is tackled from the perspective
of combinatorial optimization. Previous attempts have used
deterministic optimization techniques based on relaxation and gradient
descent-based search, and stochastic optimization techniques based on
simulated annealing and microcanonical annealing. A mathematical model
encapsulating the figure-ground separation problem that makes explicit
the definition of shape in terms of attributes such as cocircularity,
smoothness, proximity and contrast is described. The model is based on
the formulation of an energy function that incorporates pairwise
interactions between local image features in the form of edgels and is
shown to be isomorphic to the interacting spin (Ising) system from
quantum physics. This paper explores a class of stochastic optimization
techniques based on evolutionary algorithms for the problem of
figure-ground separation. A class of hybrid evolutionary stochastic
optimization algorithms based on a combination of evolutionary
algorithms, simulated annealing and microcanonical annealing are shown
to exhibit superior performance when compared to their purely
evolutionary counterparts and to classical simulated annealing and
microcanonical annealing algorithms. Experimental results on synthetic
edgel maps and edgel maps derived from gray scale images are presented.
|
360. | Ngoi, KP, and Jia, JC, "An active contour model for colour region extraction in natural scenes," IMAGE AND VISION COMPUTING, vol. 17, pp. 955-966, 1999.
Abstract:
The performance of active contours depends on the proper selection of
model parameters and initial contours. In natural scenes, active
contours often fail to converge to the desired solution because of
unconstrained environmental conditions and complex object shapes. This
paper presents a new active contour model for contour extraction in
natural scenes. The proposed model is able to extract fairly complex
object boundaries without the need to retune model parameters and image
thresholds. Specific object features and a priori knowledge of the
objects' topology are not required. Four schemes are proposed. An
attraction/repulsion scheme deforms the active contour towards the
object's boundary and makes it less sensitive to initialisation. A
positive/negative contour scheme allows closed active contours to
change their connectivity by splitting, thereby undergoing topological
changes during the deformation process. An image scale scheme and an
automatic thresholding scheme dynamically adapt the active contour in
natural scenes. The proposed model is found to outperform the original
snake model and degrade gracefully in the presence of image blur and
Gaussian noise. Object boundaries are reliably extracted from a range
of natural images. (C) 1999 Elsevier Science B.V. All rights reserved.
|
361. | Huang, PS, Harris, CJ, and Nixon, MS, "Recognising humans by gait via parametric canonical space," ARTIFICIAL INTELLIGENCE IN ENGINEERING, vol. 13, pp. 359-366, 1999.
Abstract:
Based on principal component analysis (PCA), eigenspace transformation
(EST) was demonstrated to be a potent metric in automatic face
recognition and gait analysis by template matching, but without using
data analysis to increase classification capability. Gait is a new
biometric aimed to recognise subjects by the way they walk. In this
article, we propose a new approach which combines canonical space
transformation (CST) based on Canonical Analysis (CA), with EST for
feature extraction. This method can be used to reduce data
dimensionality and to optimise the class separability of different gait
classes simultaneously. Each image template is projected from the
high-dimensional image space to a low-dimensional canonical space.
Using template matching, recognition of human gait becomes much more
accurate and robust in this new space. Experimental results on a small
database show how subjects can be recognised with 100% accuracy by
their gait, using this method. (C) 1999 Elsevier Science Ltd. All
rights reserved.
|
362. | Lee, MS, and Medioni, G, "Grouping., -, ->, theta, into regions, curves, and junctions," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 76, pp. 54-69, 1999.
Abstract:
We address the problem of extracting segmented, structured information
from noisy data obtained through local processing of images. A unified
computational framework is developed for the inference of multiple
salient structures such as junctions, curves, regions, and surfaces
from any combinations of points, curve elements, and surface patch
elements inputs in 2D and 3D. The methodology is grounded in two
elements: tensor calculus for representation and nonlinear voting for
data communication. Each input site communicates its information (a
tensor) to its neighborhood through a predefined (tensor) field and,
therefore, casts a (tensor) vote. Each site collects all the votes cast
at its location and encodes them into a new tensor. A local, parallel
routine such as a modified marching cube/square process then
simultaneously detects junctions, curves, regions, and surfaces. The
proposed method is noniterative, requires no initial guess or
thresholding, can handle the presence of multiple curves, regions, and
surfaces in a large amount of noise while it still preserves
discontinuities, and the only free parameter is scale. We present
results of curve and region inference from a variety of inputs. (C)
1999 Academic Press.
|
363. | Tiddeman, B, Rabey, G, and Duffy, N, "Synthesis and transformation of three-dimensional facial images - Extending the principles of face-space transformations by using texture-mapped laser-scanned surface data," IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, vol. 18, pp. 64-69, 1999.
Abstract:
External energies of active contours are often formulated as Euclidean
are length integrals. In this paper, we show that such formulations are
biased. By this we mean that the minimum of the external energy does
not occur at an image edge. In addition, we also show that for certain
forms of external energy the active contour is unstable-when
initialized at the true edge, the contour drifts away and becomes
jagged. Both of these phenomena are due to the use of Euclidean are
length integrals.
We propose a non-Euclidean are length which eliminates these problems.
This requires a reformulation of active contours where a single
external energy function is replaced by a sequence of energy functions
and the contour evolves as an integral curve of the gradient of these
energies. The resulting active contour not only has unbiased external
energy, but is also more controllable,
Experimental evidence is provided in support of the theoretical claims.
|
364. | Wang, KC, Dutton, RW, and Taylor, CA, "Improving geometric model construction for blood flow modeling - Geometric image segmentation and image-based model construction for computational hemodynamics," IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, vol. 18, pp. 33-39, 1999.
Abstract:
External energies of active contours are often formulated as Euclidean
are length integrals. In this paper, we show that such formulations are
biased. By this we mean that the minimum of the external energy does
not occur at an image edge. In addition, we also show that for certain
forms of external energy the active contour is unstable-when
initialized at the true edge, the contour drifts away and becomes
jagged. Both of these phenomena are due to the use of Euclidean are
length integrals.
We propose a non-Euclidean are length which eliminates these problems.
This requires a reformulation of active contours where a single
external energy function is replaced by a sequence of energy functions
and the contour evolves as an integral curve of the gradient of these
energies. The resulting active contour not only has unbiased external
energy, but is also more controllable,
Experimental evidence is provided in support of the theoretical claims.
|
365. | Ma, TY, and Tagare, HD, "Consistency and stability of active contours with Euclidean and non-Euclidean arc lengths," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 8, pp. 1549-1559, 1999.
Abstract:
External energies of active contours are often formulated as Euclidean
are length integrals. In this paper, we show that such formulations are
biased. By this we mean that the minimum of the external energy does
not occur at an image edge. In addition, we also show that for certain
forms of external energy the active contour is unstable-when
initialized at the true edge, the contour drifts away and becomes
jagged. Both of these phenomena are due to the use of Euclidean are
length integrals.
We propose a non-Euclidean are length which eliminates these problems.
This requires a reformulation of active contours where a single
external energy function is replaced by a sequence of energy functions
and the contour evolves as an integral curve of the gradient of these
energies. The resulting active contour not only has unbiased external
energy, but is also more controllable,
Experimental evidence is provided in support of the theoretical claims.
|
366. | Trevelyan, J, "Redefining robotics for the new millennium," INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, vol. 18, pp. 1211-1223, 1999.
Abstract:
This paper argues that the term "robotics" needs to be redefined as
"the science of extending human motor capabilities with machines," and
uses the author's experience with robotics over the past 25 years to
support this argument. The current definition is tied by default to the
term "robot," which emerged from science fiction-this tie needs to be
broken if robotics research is to be based on reality. The paper
reviews the author's research on sheep shearing, vision, calibration,
telerobotics, and landmine clearance, and draws some conclusions that
point to the need for changing the contemporary view of robotics. A
brief survey of subjects addressed by robotics-research journal
articles and comments from other robotics researchers support this
view. Finally, at a time when many people regard technology, and
particularly automation, with considerable skepticism, the proposed
definition is easier for ordinary people to understand and support, and
it provides more freedom for researchers to find creative approaches.
|
367. | Sim, HC, and Damper, RI, "A neural network approach to planar-object recognition in 3D space," PATTERN ANALYSIS AND APPLICATIONS, vol. 2, pp. 143-163, 1999.
Abstract:
Most existing 2D object recognition algorithms are not perspective (or
projective) invariant, and hence are not suitable far many real-world
applications. By contrast, one of the primary goals of this research is
to develop a flat object matching system that can identify and localise
an object, even when seen from different viewpoints in 3D space. In
addition, we also strive to achieve good scale invariance and
robustness against partial occlusion as in any practical 2D object
recognition system. The proposed system uses multi-view model
representations and objects are recognised by self-organised dynamic
link matching. The merit of this approach is that: it offers a compact
framework for concurrent assessments of multiple match hypotheses by
promoting competitions and/or co-operations among several local
mappings of model and test image feature correspondences. Our
experiments show that the system is very successful in recognising
object to perspective distortion, even in rather cluttered scenes.
|
368. | Wolberg, WH, Street, WN, and Mangasarian, OL, "Importance of nuclear morphology in breast cancer prognosis," CLINICAL CANCER RESEARCH, vol. 5, pp. 3542-3548, 1999.
Abstract:
The purpose of this study is to define prognostic relationships between
computer-derived nuclear morphological features, lymph node status, and
tumor size in breast cancer. Computer-derived nuclear size, shape, and
texture features were determined in fine-needle aspirates obtained at
the time of diagnosis from 253 consecutive patients with invasive
breast cancer. Tumor size and lymph node status were determined at the
time of surgery, Median follow-up time was 61.5 months for patients
without distant recurrence, In univariate analysis, tumor size, nuclear
features, and the number of metastatic nodes were of decreasing
significance for distant disease-free survival. Nuclear features, tumor
size, and the number of metastatic nodes were of decreasing
significance for overall survival. In multivariate analysis, the
morphological size feature, largest perimeter, was more predictive of
disease-free and overall survival than were either tumor size or the
number of axillary lymph node metastases. This morphological feature,
when combined with tumor size, identified more patients at both the
good and poor ends of the prognostic spectrum than did the combination
of tumor size and axillary lymph node status, Our data indicate that
computer analysis of nuclear features has the potential to replace
axillary lymph node status for staging of breast cancer. If confirmed
by others, axillary dissection for breast cancer staging, estimating
prognosis, and selecting patients for adjunctive therapy could be
eliminated.
|
369. | Chesnaud, C, Refregier, P, and Boulet, V, "Statistical region snake-based segmentation adapted to different physical noise models," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 21, pp. 1145-1157, 1999.
Abstract:
Algorithms for object segmentation are crucial in many image processing
applications. During past years, active contour models (snakes) have
been widely used for finding the contours of objects. This segmentation
strategy is classically edge-based in the sense that the snake is
driven to fit the maximum of an edge map of the scene. In this paper,
we propose a region snake approach and we determine fast algorithms for
the segmentation of an object in an image. The algorithms developed in
a Maximum Likelihood approach are based on the calculation of the
statistics of the inner and the outer regions (defined by the snake).
It has thus been possible to develop optimal algorithms adapted to the
random fields which describe the gray levels in the input image if we
assume that their probability density function family are known. We
demonstrate that this approach is still efficient when no boundary's
edge exists in the image. We also show that one can obtain fast
algorithms by transforming the summations over a region, for the
calculation of the statistics, into summations along the boundary of
the region. Finally, we will provide numerical simulation results for
different physical situations in order to illustrate the efficiency of
this approach.
|
370. | Gotte, MJW, van Rossum, AC, Marcus, JT, Kuijer, JPA, Axel, L, and Visser, CA, "Recognition of infarct localization by specific changes in intramural myocardial mechanics," AMERICAN HEART JOURNAL, vol. 138, pp. 1038-1045, 1999.
Abstract:
Background After transmural myocardial infarction (MI), changes occur
in intramural myocardial function. This has been described in anterior
MI only. The aim of this study was to determine the relation between
variable infarct locations and intramural deformation in patients with
a first MI.
Methods Forty patients (33 men and 7 women aged 57 +/- 11 years) with
different infarct-related coronary arteries 125 left anterior
descending, 7 circumflex, and 8 right coronary) were studied 6 +/- 3
days after infarction with magnetic resonance tissue tagging and
2-dimensional finite element analysis of myocardial deformation.
Short-axis tagged images were acquired at base, mid, and apical level.
Intramural deformation was measured in 6 circumferential segments per
level. Results were compared with 9 age-matched healthy controls.
Results Each infarct area demonstrated a-significant reduction of
intramural deformation. At mid-ventricular level, segments with maximum
impaired intramural function were the anteroseptal segment for left
anterior descending-related MI (stretch: 16% vs 33% for controls, P <
.001), the posterolateral segment for related MI (stretch: 20% vs 34%,
P < .01); and the inferior segment for right coronary artery related MI
(stretch: 18% vs 25%, P = .082). In these infarct segments, the
intramural regional systolic stretch was more circumferentially
oriented compared with radilly oriented stretch in the same segments in
controls (P < .05).
Conclusion The infarct area can be recognized by a specific spatial
pattern of intramural deformation, In infarcted compared with
noninfarcted myocardium, deformation is significantly reduced and
systolic stretch deviates from the radial direction. Left anterior
descending related infarcts were found to have larger regional
differences in intramural deformation than circumflex or right coronary
artery related MI of enzymatically the same size.
|
371. | Zhong, D, and Chang, SF, "An integrated approach for content-based video object segmentation and retrieval," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol. 9, pp. 1259-1268, 1999.
Abstract:
Object-based video data representations enable unprecedented
functionalities of content access and manipulation. In this paper, we
present an integrated approach using region-based analysis for semantic
video object segmentation and retrieval. We first present an active
system that combines low-level region segmentation with user inputs for
defining and tracking semantic video objects. The proposed technique is
novel in using an integrated feature fusion framework for tracking and
segmentation at both region and object levels. Experimental results and
extensive performance evaluation show excellent results compared to
existing systems. Building upon the segmentation framework, we then
present a unique region-based query system for semantic video object.
The model facilitates powerful object search, such as spatio-temporal
similarity searching at multiple levels.
|
372. | Shekhar, R, Cothren, RM, Vince, DG, Chandra, S, Thomas, JD, and Cornhill, JF, "Three-dimensional segmentation of luminal and adventitial borders in serial intravascular ultrasound images," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 23, pp. 299-309, 1999.
Abstract:
Intravascular ultrasound (IVUS) provides exact anatomy of arteries,
allowing accurate quantitative analysis. Automated segmentation of IVUS
images is a prerequisite for routine quantitative analyses. We present
a new three-dimensional (3D) segmentation technique, called active
surface segmentation, which detects luminal and adventitial borders in
IVUS pullback examinations of coronary arteries. The technique was
validated against expert tracings by computing correlation coefficients
(range 0.83-0.97) and William's index values (range 0.37-0.66), The
technique was statistically accurate, robust to image artifacts, and
capable of segmenting a large number of images rapidly. Active surface
segmentation enabled geometrically accurate 3D reconstruction and
visualization of coronary arteries and volumetric measurements. (C)
1999 Elsevier Science Ltd. All rights reserved.
|
373. | Akgul, YS, Kambhamettu, C, and Stone, M, "Automatic extraction and tracking of the tongue contours," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 1035-1045, 1999.
Abstract:
Computerized analysis of the tongue surface movement can provide
valuable information to speech and swallowing research. Ultrasound
technology is currently the most attractive modality for the tongue
imaging mainly because of its high video frame rate. However, problems
with ultrasound imaging, such as noise and echo artifacts, refractions,
and unrelated reflections pose significant challenges for computer
analysis of the tongue images and hence specific methods must be
developed.
This paper presents a system that is developed for automatic extraction
and tracking of the tongue surface movements from ultrasound image
sequences. The ultrasound images are supplied by the head and
transducer support system (HATS), which was developed in order to fix
the head and support the transducer under the chin in a known position
without disturbing speech, In this work, we propose a novel scheme for
the analysis of the tongue images using deformable contours. We
incorporate novel mechanisms to 1) impose speech related constraints on
the deformations; 2) perform spatiotemporal smoothing using a contour
postprocessing stage; 3) utilize optical flow techniques to speedup the
search process; and 4) propagate user supplied information to the
analysis of all image frames.
We tested the system's performance qualitatively and quantitatively in
consultation with speech scientists. Our system produced contours that
are within the range of manual measurement variations. The results of
our system are extremely encouraging and the system can be used in
practical speech and swallowing research in the field of otolaryngology.
|
374. | Hagemann, A, Rohr, K, Stiehl, HS, Spetzger, U, and Gilsbach, JM, "Biomechanical modeling of the human head for physically based, nonrigid image registration," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 875-884, 1999.
Abstract:
The accuracy of image-guided neurosurgery generally suffers from brain
deformations due to intraoperative changes. These deformations cause
significant changes of the anatomical geometry (organ shape and spatial
interorgan relations), thus making intraoperative navigation based on
preoperative images error prone. In order to improve the navigation
accuracy, we developed a biomechanical model of the human head based on
the finite element method, which can be employed for the correction of
preoperative images to cope with the deformations occurring during
surgical interventions. At the current stage of development, the
two-dimensional (2-D) implementation of the model comprises two
different materials, though the theory holds for the three-dimensional
(3-D) case and is capable of dealing with an arbitrary number of
different materials. For the correction of a preoperative image, a set
of homologous landmarks must be specified which determine
correspondences. These correspondences can be easily integrated into
the model and are maintained throughout the computation of the
deformation of the preoperative image. The necessary material parameter
values have been determined through a comprehensive literature study.
Our approach has been tested for the case of synthetic images and
yields physically plausible deformation results. Additionally, we
carried out registration experiments with a preoperative MR image of
the human head and a corresponding postoperative image simulating an
intraoperative image. We found that our approach yields good prediction
results, even in the case when correspondences are given in a
relatively small area of the image only.
|
375. | McInerney, T, and Terzopoulos, D, "Topology adaptive deformable surfaces for medical image volume segmentation," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 840-850, 1999.
Abstract:
Deformable models, which include deformable contours (the popular
snakes) and deformable Surfaces, are a powerful model-based medical
image analysis technique. We develop a new class of deformable models
by formulating deformable surfaces in terms of an affine cell image
decomposition (ACID). Our approach significantly extends standard
deformable surfaces, while retaining their interactivity and other
desirable properties. In particular, the ACID induces an efficient
reparameterization mechanism that enables parametric deformable
surfaces to evolve into complex geometries, even modifying their
topology as necessary. We demonstrate that our new ACID-based
deformable surfaces, dubbed T-surfaces, can effectively segment complex
anatomic structures from medical volume images.
|
376. | Kelemen, A, Szekely, G, and Gerig, G, "Elastic model-based segmentation of 3-D neuroradiological data sets," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 828-839, 1999.
Abstract:
This paper presents a new technique for the automatic model-based
segmentation of three-dimensional (3-D) objects from volumetric image
data. The development closely follows the seminal work of Taylor and
Cootes on active shape models, but is based on a hierarchical
parametric object description rather than a point distribution model,
The segmentation system includes both the building of statistical
models and the automatic segmentation of new image data sets via a
restricted elastic deformation of shape models, Geometric models are
derived from a sample set of image data which have been segmented by
experts, The surfaces of these binary objects are converted into
parametric surface representations, which are normalized to get an
invariant object-centered coordinate system, Surface representations
are expanded into series of spherical harmonics which provide
parametric descriptions of object shapes. It is shown that invariant
object surface parametrization provides a good approximation to
automatically determine object homology in terms of sets of
corresponding sets of surface points. Gray-level information near
object boundaries is represented by 1-D intensity profiles normal to
the surface. Considering automatic segmentation of brain structures as
our driving application, our choice of coordinates for object alignment
was the well-accepted stereotactic coordinate system. Major variation
of object shapes around the mean shape, also referred to as shape
eigenmodes, are calculated in shape parameter space rather than the
feature space of point coordinates, Segmentation makes use of the
object shape statistics by restricting possible elastic deformations
into the range of the training shapes, The mean shapes are initialized
in a new data set by specifying the landmarks of the stereotactic
coordinate system, The model elastically deforms, driven by the
displacement forces across the object's surface, which are generated by
matching local intensity profiles. Elastical deformations are limited
by setting bounds for the maximum variations in eigenmode space. The
technique has been applied to automatically segment left and right
hippocampus, thalamus, putamen, and globus pallidus from volumetric
magnetic resonance scans taken from schizophrenia studies. The results
have been validated by comparison of automatic segmentation with the
results obtained by interactive expert segmentation.
|
377. | Olver, PJ, Sapiro, G, and Tannenbaum, A, "Affine invariant detection: Edge maps, anisotropic diffusion, and active contours," ACTA APPLICANDAE MATHEMATICAE, vol. 59, pp. 45-77, 1999.
Abstract:
In this paper we undertake a systematic investigation of affine
invariant object detection and image denoising. Edge detection is first
presented from the point of view of the affine invariant scale-space
obtained by curvature based motion of the image level-sets. In this
case, affine invariant maps are derived as a weighted difference of
images at different scales. We then introduce the affine gradient as an
affine invariant differential function of lowest possible order with
qualitative behavior similar to the Euclidean gradient magnitude. These
edge detectors are the basis for the extension of the affine invariant
scale-space to a complete affine flow for image denoising and
simplification, and to define affine invariant active contours for
object detection and edge integration. The active contours are obtained
as a gradient flow in a conformally Euclidean space defined by the
image on which the object is to be detected. That is, we show that
objects can be segmented in an affine invariant manner by computing a
path of minimal weighted affine distance, the weight being given by
functions of the affine edge detectors. The gradient path is computed
via an algorithm which allows to simultaneously detect any number of
objects independently of the initial curve topology. Based on the same
theory of affine invariant gradient flows we show that the affine
geometric heat flow is minimizing, in an affine invariant form, the
area enclosed by the curve.
|
378. | Terzopoulos, D, "Visual modeling for multimedia content," ADVANCED MULTIMEDIA CONTENT PROCESSING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1554, pp. 406-421, 1999.
Abstract:
This paper reviews research that addresses the challenging problem of
modeling living systems for multimedia content creation. First, I
discuss the modeling of animals in their natural habitats for use in
animated virtual worlds. The basic approach is to implement realistic
artificial animals (in particular, fish) and to give them the ability
to locomote, perceive, and in some sense understand the realistic
virtual worlds in which they are situated so that they may achieve both
individual and social functionality within these worlds. Second, I
discuss the modeling of human faces. The goal is to develop facial
models that are capable of synthesizing realistic expressions. At
different levels of abstraction, these hierarchical models capture
knowledge from psychology, facial anatomy and tissue histology, and
continuum biomechanics. The facial models can be "personalized", or
made to conform closely to individuals, once facial geometry and
photometry information has been captured by a range sensor.
|
379. | Mortensen, EN, "Vision-assisted image editing," COMPUTER GRAPHICS-US, vol. 33, pp. 55-57, 1999.
Abstract:
A CNN-based algorithm for image segmentation by active contours is
proposed here. The algorithm is based on an iterative process of
expansion of the contour and its subsequent thinning guided by external
and internal energy. The proposed strategy allows for a high level of
control over contour evolution making their topologic transformations
easier. Therefore processing of multiple contours for segmenting
several objects can be carried out simultaneously.
|
380. | Kozek, T, and Vilarino, DL, "An active contour algorithm for continuous-time cellular neural networks," JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, vol. 23, pp. 403-414, 1999.
Abstract:
A CNN-based algorithm for image segmentation by active contours is
proposed here. The algorithm is based on an iterative process of
expansion of the contour and its subsequent thinning guided by external
and internal energy. The proposed strategy allows for a high level of
control over contour evolution making their topologic transformations
easier. Therefore processing of multiple contours for segmenting
several objects can be carried out simultaneously.
|
381. | Rekeczky, C, and Chua, LO, "Computing with front propagation: Active contour and skeleton models in continuous-time CNN," JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, vol. 23, pp. 373-402, 1999.
Abstract:
In this paper, a linear CNN template class is studied with a symmetric
feedback matrix capable of generating trigger-waves, a special type of
binary traveling-wave. The qualitative properties of these waves are
examined and some simple control strategies are derived based on
modifying the bias and feedback terms in a CNN template. It is shown
that a properly controlled wave-front can be efficiently used in
segmentation, shape and structure detection/recovery tasks. Shape is
represented by the contour of an evolving front. An algorithmic
framework is discussed that incorporates bias controlled trigger-waves
in tracking the active contour of the objects during rigid and
non-rigid motion. The object skeleton (structure) is obtained as a
composition of stable annihilation lines formed during the collision of
trigger wave-fronts. The shortest path problem in a binary labyrinth is
also formulated as a special type of skeletonization task and solved by
combined trigger-wave based techniques.
|
382. | Velasco, HMG, Aligue, FJL, Orellana, CJG, Macias, MM, and Sotoca, MIA, "Application of ANN techniques to automated identification of bovine livestock," ENGINEERING APPLICATIONS OF BIO-INSPIRED ARTIFICIAL NEURAL NETWORKS, VOL II, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1607, pp. 422-431, 1999.
Abstract:
In this work a classification system is presented that, taking lateral
images of cattle as inputs, is able to identify the animals and
classify them by breed into previously learnt classes. The system
consists of two fundamental parts. In the first one, a
deformable-model-based preprocessing of the image is made, in which the
contour of the animal in the photograph is sought, extracted, and
normalized. Next, a neural classifier is presented that, supplemented
with a decision-maker at its output, makes the distribution into
classes. In the last part, the results obtained in a real application
of this methodology are presented.
|
383. | Chella, A, Di Gesu, V, Infantino, I, Intravaia, D, and Valenti, C, "A cooperating strategy for objects recognition," SHAPE, CONTOUR AND GROUPING IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1681, pp. 264-274, 1999.
Abstract:
The paper describes an object recognition system, based on the
co-operation of several visual modules (early vision, object detector,
and object recognizer). The system is active because the behavior of
each module is tuned on the results given by other modules and by the
internal models. This solution allows to detect inconsistencies and to
generate a feedback process. The proposed strategy has shown good
performance especially in case of complex scene analysis, and it has
been included in the visual system of the DAISY robotics system.
Experimental results on real data are also reported.
|
384. | Doucette, P, Agouris, P, Musavi, M, and Stefanidis, A, "Automated extraction of linear features from aerial imagery using Kohonen learning and GIS data," INTEGRATED SPATIAL DATABASES: DIGITAL IMAGES AND GIS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1737, pp. 20-33, 1999.
Abstract:
An approach to semi-automated linear feature extraction from aerial
imagery is introduced in which Kohonen's self-organizing map (SOM)
algorithm is integrated with existing GIS data. The SOM belongs to a
distinct class of neural networks which is characterized by competitive
and unsupervised learning. Using radiometrically classified image
pixels as input, appropriate SOM network topologies are modeled to
extract underlying spatial structures contained in the input patterns.
Coarse-resolution GIS vector data is used for network weight and
topology initialization when extracting specific feature components.
The Kohonen learning rule updates the synaptic weight vectors of
winning neural units that represent 2-D vector shape vertices.
Experiments with high-resolution hyperspectral imagery demonstrate a
robust ability to extract centerline information when presented with
coarse input.
|
385. | Laading, JK, McCulloch, C, Johnson, VE, Gilland, DR, and Jaszczak, RJ, "A hierarchical feature based deformation model applied to 4D cardiac SPECT data," INFORMATION PROCESSING IN MEDICAL IMAGING, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1613, pp. 266-279, 1999.
Abstract:
In this paper we describe a statistical model for the observation of
labeled points in gated cardiac single photon emission computed
tomography (SPECT) images. The model has two major parts: one based on
shape correspondence between the image for evaluation and a reference
image, and a second based on the match in image features. While the
statistical deformation model is applicable to a broad range of image
objects, the addition of a contraction mechanism to the baseline model
provides particularly convincing results in gated cardiac SPECT. The
model is applied to clinical data and provides marked improvement in
the quality of summary images for the time series. Estimates of heart
deformation and contraction parameters are also obtained.
|
386. | Chung, DH, and Sapiro, G, "A windows-based user friendly system for image analysis with partial differential equations," SCALE-SPACE THEORIES IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1682, pp. 453-458, 1999.
Abstract:
In this paper we present and briefly describe a Windows user-friendly
system designed to assist with the analysis of images in general, and
biomedical images in particular. The system, which is being made
publicly available to the research community, implements basic 2D image
analysis operations based on partial differential equations (PDE's).
The system is under continuous development, and already includes a
large number of image enhancement and segmentation routines that have
been tested for several applications.
|
387. | Sifakis, E, and Tziritas, G, "Fast marching to moving object location," SCALE-SPACE THEORIES IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1682, pp. 447-452, 1999.
Abstract:
In this paper we address two important problems in motion analysis: the
detection of moving objects and their localization. Statistical and
level set approaches are adopted in order to formulate these problems.
For the change detection problem, the inter-frame difference is modeled
by a mixture of two zero-mean Laplacian distributions. At first,
statistical tests using criteria with negligible error probability axe
used for labeling as many as possible sites as changed or unchanged.
All the connected components of the labeled sites are seed regions,
which give the initial level sets, for which velocity fields for label
propagation are provided. We introduce a new multi-label fast marching
algorithm for expanding competitive regions. The solution of the
localization problem is based on the map of changed pixels previously
extracted. The boundary of the moving object is determined by a level
set algorithm, which is initialized by two curves evolving in
converging opposite directions. The sites of curve contact determine
the position of the object boundary. For illustrating the efficiency of
the proposed approach, experimental results are presented using real
video sequences.
|
388. | Chan, T, and Vese, L, "An active contour model without edges," SCALE-SPACE THEORIES IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1682, pp. 141-151, 1999.
Abstract:
In this paper, we propose a new model for active contours to detect
objects in a given image, based on techniques of curve evolution,
Mumford-Shah functional for segmentation and level sets. Our model can
detect objects whose boundaries are not necessarily defined by
gradient. The model is a combination between more classical active
contour models using mean curvature motion techniques, and the
Mumford-Shah model for segmentation. We minimize an energy which can be
seen as a particular case of the so-called minimal partition problem.
In the level set formulation, the problem becomes a "mean-curvature
flow" -like evolving the active contour, which will stop on the desired
boundary. However, the stopping term does not depend on the gradient of
the image, as in the classical active contour models, but is instead
related to a particular segmentation of the image. Finally, we will
present various experimental results and in particular some examples
for which the classical snakes methods based on the gradient are not
applicable.
|
389. | Gomes, J, and Faugeras, O, "Reconciling distance functions and level sets," SCALE-SPACE THEORIES IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1682, pp. 70-81, 1999.
Abstract:
This paper is concerned with the simulation of the Partial Differential
Equation (PDE) driven evolution of a closed surface by means of an
implicit representation. In most applications, the natural choice for
the implicit representation is the signed distance function to the
closed surface. Osher and Sethian propose to evolve the distance
function with a Hamilton-Jacobi equation. Unfortunately the solution to
this equation is not a distance function. As a consequence, the
practical application of the level set method is plagued with such
questions as when do we have to "reinitialize" the distance function?
How do we "reinitialize" the distance function? Etc... which reveal a
disagreement between the theory and its implementation. This paper
proposes an alternative to the use of Hamilton-Jacobi equations which
eliminates this contradiction: in our method the implicit
representation always remains a distance function by construction, and
the implementation does not differ from the theory anymore. This is
achieved through the introduction of a new equation. Besides its
theoretical advantages, the proposed method also has several practical
advantages which we demonstrate in two applications: (i) the
segmentation of the human cortex surfaces from MRI images using two
coupled surfaces [26], (ii) the construction of a hierarchy of
Euclidean skeletons of a 3D surface.
|
390. | Bertalmio, M, Sapiro, G, and Randall, G, "Morphing active contours," SCALE-SPACE THEORIES IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1682, pp. 46-57, 1999.
Abstract:
A method for deforming curves in a given image to a desired position in
a second image is introduced in this paper. The algorithm is based on
deforming the first image toward the second one via a partial
differential equation, while tracking the deformation of the curves of
interest in the first image with an additional, coupled, partial
differential equation. The tracking is performed by projecting the
velocities of the first equation into the second one. In contrast with
previous PDE based approaches, both the images and the curves on the
frames/slices of interest axe used for tracking. The technique can be
applied to object tracking and sequential segmentation. The topology of
the deforming curve can change, without any special topology handling
procedures added to the scheme. This permits for example the automatic
tracking of scenes where, due to occlusions, the topology of the
objects of interest changes from frame to frame. In addition, this work
introduces the concept of projecting velocities to obtain systems of
coupled partial differential equations for image analysis applications.
We show examples for object tracking and segmentation of electronic
microscopy. We also briefly discuss possible uses of this framework for
three dimensional morphing.
|
391. | Goldenberg, R, Kimmel, R, Rivlin, E, and Rudzsky, M, "Fast geodesic active contours," SCALE-SPACE THEORIES IN COMPUTER VISION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1682, pp. 34-45, 1999.
Abstract:
We use an unconditionally stable numerical scheme to implement a fast
version of the geodesic active contour model. The proposed scheme is
useful for object segmentation in images, like tracking moving objects
in a sequence of images. The method is based on the
Weickert-Romeney-Viergever [33] AOS scheme. It is applied at small
regions, motivated by Adalsteinsson-Sethian [1] level set narrow band
approach, and uses Sethian's fast marching method [26] for
re-initialization. Experimental results demonstrate the power of the
new method for tracking in color movies.
|
392. | Katahara, S, and Aoki, M, "Face parts extraction window based on bilateral symmetry of gradient direction," COMPUTER ANALYSIS OF IMAGES AND PATTERNS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1689, pp. 489-497, 1999.
Abstract:
We propose a simple algorithm to determine face parts extraction window
in face image. We utilize bilateral symmetries between and within face
parts. We also use knowledge about size and locationship of face parts.
First, we examine bilateral symmetries around vertical orientation
edge, then obtain symmetry measures. The symmetry measures are
projected onto y-axis to produce histogram of the measures. We estimate
height of face parts regions by frequency of the histogram. Face parts
region, which contains maximum frequency of the histogram, becomes a
candidate of face parts region that includes eyes and eyebrows.
Secondly, the measures that exist within the height of the face parts
region are projected onto x-axis to estimate width of face parts
region. We determine face parts extraction windows by the estimated
height and width. Finally. we detect irises in the candidate of face
parts region that includes eyes and eyebrows, using circular mask.
|
393. | Klemencic, A, Pernus, F, and Kovacic, S, "Modeling morphological changes during contraction of muscle fibres by active contours," COMPUTER ANALYSIS OF IMAGES AND PATTERNS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1689, pp. 134-141, 1999.
Abstract:
An active contour model with expansion "balloon" forces was used as a
tool to simulate the changes in shape and increase in cross-sectional
area, which occur during the contraction of isolated muscle fiber. A
polygon, imitating the boundaries of the relaxed muscle fiber
cross-section. represented the initial position of the active contour
model. This contour was then expanded in order to increase the
cross-sectional area and at the same time intrinsic elastic properties
smoothed the contour. The process of expansion was terminated, when the
area of the inflated contour surpassed the preset value. The equations
that we give, lead to a controlled expansion of the active contour
model.
|
394. | Berger, MO, Winterfeldt, G, and Lethor, JP, "Contour tracking in echo cardiographic sequences without learning stage: Application to the 3D reconstruction of the beating left ventricule," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, MICCAI'99, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1679, pp. 508-515, 1999.
Abstract:
In this paper we present a contour tracker oil echographic image
sequences. To do this, we use a hierarchical approach: we first compute
a global estimation of the ventricular motion. Then we use a fine
tuning algorithm to adjust the detection of the ventricular wall. The
global estimation is based oil a parametric motion model with a small
number of parameters. This allows us to compute the motion in a robust
way from the velocity computed at each point of the contour.
Results are presented demonstrating tracking on various echographic
sequences. We conclude by discussing some of our current research
efforts.
|
395. | Montagnat, J, Delingette, H, and Malandain, G, "Cylindrical echocardiographic image segmentation based on 3D deformable models," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, MICCAI'99, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1679, pp. 168-175, 1999.
Abstract:
This paper presents a 3D echocardiographic image segmentation procedure
based on deformable surfaces. We first propose to adapt filtering
techniques to the cylindrical geometry of several 3D ultrasound image
devices. Then we compare the effect of different external forces on a
surface template deformation inside volumetric echocardiographic
images. An original method involving region grey-level analysis along
the model normal directions is described. We rely on an a priori
knowledge of the cardiac left ventricle shape and on region grey-level
values to perform a robust segmentation. During the deformation process
the allowable surface deformation is modified. Finally, we show
experimental results on very challenging sparse and noisy images and
quantitative measurements of the left ventricle volume.
|
396. | Liang, JM, McInerney, T, and Terzopoulos, D, "Interactive medical image segmentation with United Snakes," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, MICCAI'99, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1679, pp. 116-127, 1999.
Abstract:
Snakes have become a standard image analysis technique with several
variants now in common use. We have developed a software package called
"United Snakes". It unifies the most important snake variants,
including finite difference, B-spline, and Hermite polynomial snakes,
within the framework of a general finite element formulation with a
choice of shape functions. Furthermore, we have incorporated into
united snakes a recently proposed snake-like technique known as
"livewire", via a method for imposing hard constraints on snakes. Here,
we demonstrate that the combination of techniques in united snakes
yields generality, accuracy, ease of use, and robustness in several
medical image analysis applications, including the segmentation of
neuronal dendrites in EM images, dynamic chest image analysis, and the
quantification of growth plates.
|
397. | Hug, J, Brechbuhler, C, and Szekely, G, "Tamed Snake: A particle system for robust semi-automatic segmentation," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, MICCAI'99, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1679, pp. 106-115, 1999.
Abstract:
Semi-automatic segmentation approaches tend to overlook the problems
caused by missing or incomplete image information. In such situations,
powerful control mechanisms and intuitive modelling metaphors should be
provided in order to make the methods practically applicable. Taking
this problem into account, the usage of subdivision curves in
combination with the simulation of edge attracted mass points is
proposed as a novel way towards a more robust interactive segmentation
methodology. Subdivision curves provide a hierarchical and smooth
representation of a shape which call be modified on coarse and on fine
scales as well. Furthermore, local adaptive subdivision gives the
required flexibility when dealing with a discrete curve representation.
III order to incorporate image information, the control vertices of a
curve are considered mass points, attracted by edges in the local
neighbourhood of the image. This so-called Tamed Snake framework is
illustrated by means of the segmentation of two medical data sets and
the results are compared with those achieved by traditional Snakes.
|
398. | Bajaj, CL, Chen, JD, Holt, RJ, and Netravali, AN, "Energy formulations of A-splines," COMPUTER AIDED GEOMETRIC DESIGN, vol. 16, pp. 39-59, 1999.
Abstract:
A-splines are implicit real algebraic curves in Bernstein-Bezier (BB)
form that are smooth. We develop A-spline curve models using various
energy formulations, incorporating bending and stretching energy, based
on the theory of elasticity. The attempt to find true energy minimizing
curves usually leads to complicated integrals which can only be solved
numerically, we introduce a simplified energy formulation which is much
faster to compute yet still provides reasonably accurate results.
Several examples for C-1-continuous quadratic A-splines using the true
and simplified energy models are then presented. (C) 1999 Elsevier
Science B.V. All rights reserved.
|
399. | Liao, CW, and Medioni, G, "Simultaneous surface approximation and segmentation of complex objects," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 73, pp. 43-63, 1999.
Abstract:
Deformable models represent a useful approach to approximate objects
from collected data points. We propose to augment the basic approaches
designed to handle mostly compact objects or objects of known topology.
Our approach can fit simultaneously more than one curve or surface to
approximate multiple topologically complex objects by using (1) the
residual data points, (2) the badly fitting parts of the approximating
surface, and (3) appropriate Boolean operations. In 2-D, B-snakes [3]
are used to approximate each object (pattern). In 3-D, an analytical
surface representation, based on the elements detected, is presented.
The global representation of a 3-D object, in terms of elements and
their connection, takes the form of B-spline and Bezier surfaces. A
Bezier surface is used to connect different elements, and the
connecting surface itself conforms to the data points nearby through
energy minimization. This way, a G(1) continuity surface is achieved
for the underlying 3-D object.
We present experiments on synthetic and real data in 2-D and 3-D. In
these experiments, multiple complex patterns and objects with through
holes are segmented. The system proceeds automatically without human
interaction or any prior knowledge of the topology of the underlying
object. (C) 1999 Academic Press.
|
400. | Yuan, C, Lin, E, Millard, J, and Hwang, JN, "Closed contour edge detection of blood vessel lumen and outer wall boundaries in black-blood MR images," MAGNETIC RESONANCE IMAGING, vol. 17, pp. 257-266, 1999.
Abstract:
Quantitative measurements of the blood vessel wall area may provide
useful information of atherosclerotic plaque burden, progression and/or
regression. Magnetic resonance imaging is a promising technique for
identifying both luminal and outer wall boundaries of the human blood
vessels. Currently these boundaries are primarily defined manually, a
process viewed as labor intensive and subject to significant operator
bias. Fully automated post-processing techniques used for identifying
the lumen and wall boundaries, on the other hand, are also problematic
due to the complexity of signal features in the vicinity of the blood
vessels. The goals of this study were to develop a robust, automated
closed contour edge detection algorithm, apply this algorithm to high
resolution human carotid artery images, and assess its accuracy, and
reproducibility, Our algorithm has proven to be sensitive to various
contrast situations and is reasonably accurate and highly reproducible.
(C) 1999 Elsevier Science Inc.
|
401. | Scott, CH, Sutton, MS, Gusani, N, Fayad, Z, Kraitchman, D, Keane, MG, Axel, L, and Ferrari, VA, "Effect of dobutamine on regional left ventricular function measured by tagged magnetic resonance imaging in normal subjects," AMERICAN JOURNAL OF CARDIOLOGY, vol. 83, pp. 412-417, 1999.
Abstract:
The effect of inotropic stimulation on the pattern and magnitude of
regional left ventricular contraction was studied using tagged magnetic
resonance imaging to assess whether dobutamine exacerbates variation in
regional contraction at rest. Dobutamine stress testing defines a
normal response as a homogeneous increase in regional wall motion. in 8
normal subjects, 4 equally spaced left ventricular short-axis levels
were imaged through systole using tagged magnetic resonance imaging.
The baseline imaging sequence was repeated with 5-, 10-, 15-, and 20-mu
g/kg/min dobutamine infusion. Regional myocardial displacement redial
thickening, and circumferential shortening were measured. The left
ventricle was analyzed by level (base to apex) and wall (septum,
inferior, lateral, anterior), Dobutamine did not alter baseline
regional functional heterogeneity. Dobutamine infusion resulted in a
uniform increase in displacement, radial thickening, and
circumferential shortening from baseline to 10-mu g/kg/min infusion
without additional increases at higher doses. (C) 1999 by Excerpta
Medica, Inc.
|
402. | Gee, JC, "On matching brain volumes," PATTERN RECOGNITION, vol. 32, pp. 99-111, 1999.
Abstract:
To characterize the complex morphological variations that occur
naturally in human neuroanatomy so that their confounding effect can be
minimized in the identification of brain structures in medical images,
a computational framework has evolved in which individual anatomies are
modeled as warped versions of a canonical representation of the
anatomy, known as an atlas. To realize this framework, the method of
elastic matching was invented for determining the spatial mapping
between a three-dimensional image pair in which one image volume is
modeled as an elastic continuum that is deformed to match the
appearance of the second volume. In this paper, we review the seminal
ideas underlying the elastic matching technique, consider the practical
implications of an integral formation of the approach, and explore a
more general Bayesian interpretation of the method in order to address
issues that are less naturally resolved within a continuum mechanical
setting, such as the examination of a solution's reliability or the
incorporation of empirical information that may be available about the
spatial mappings into the analysis. (C) 1999 Pattern Recognition
Society. Published by Elsevier Science Ltd. All rights reserved.
|
403. | Marchant, JA, Schofield, CP, and White, RP, "Pig growth and conformation monitoring using image analysis," ANIMAL SCIENCE, vol. 68, pp. 141-150, 1999.
Abstract:
Machine vision can be used to collect images of pigs and analyse them
to identify and measure specific areas and dimensions related to their
growth, shape and hence conformation. This information could improve
the stockman's ability to maximize production efficiency and also to
monitor health by defecting abnormalities in growth rates. This work
introduces fully automated algorithms which find the plan view outline
of animals in a normal housing situation, divide the outline into major
body components and measure specified dimensions and areas. Special
attention is paid to determining whether the results are sufficiently
repeatable to be useful in estimating these parameters. Problems in
compensating for changes in the optical geometry are outlined and
methods proposed to deal with them. The repeatability of the image
analysis process coupled with the subsequent signal processing for
outlier rejection gives s.e. values on areas of < 0.005 and on linear
dimensions of < 0.0025. For example the plan view area less head and
neck (A4) can be used to predict the weight of the group of pigs at 34
kg, 66 kg and 98 kg with standard errors of 0.25 kg, 0.17 kg and 0.39
kg respectively when using manual weighing results to calibrate the
system. If an individual pig is weighed once at 75 days (e.g. 34 kg) to
calibrate the A4-to-weight relationship, subsequent A4 measurements can
be used to predict its weight when 125 days old (approx. 80 kg) to
within l kg. This matches the accuracy of the manual weighing system
used in the trials. The effect of pig gender on the area to weight
relationships is not significant (P = 0.074), but there is a small yet
significant gender effect with the linear dimensions.
|
404. | Post, FH, de Leeuw, WC, Sadarjoen, IA, Reinders, F, and van Walsum, T, "Global, geometric, and feature-based techniques for vector field visualization," FUTURE GENERATION COMPUTER SYSTEMS, vol. 15, pp. 87-98, 1999.
Abstract:
Vector field visualization techniques are subdivided into three
categories: global, geometric, and feature-based techniques. We
describe each category, and we present some related work and an example
in each category from our own recent research. Spot noise is a texture
synthesis technique for global visualization of vector fields on 2D
surfaces. Deformable surfaces is a generic technique for extraction and
Visualization of geometric objects (surfaces or volumes) in 3D data
fields. Selective and iconic visualization is an approach that extracts
important regions or structures from large data sets, calculates
high-level attributes, and visualizes the features using parameterized
iconic objects. It is argued that for vector fields a range of
Visualization techniques are needed to fulfill the needs of the
application. (C) 1999 Published by Elsevier Science B.V. All rights
reserved.
|
405. | Davatzikos, C, and Prince, JL, "Convexity analysis of active contour problems," IMAGE AND VISION COMPUTING, vol. 17, pp. 27-36, 1999.
Abstract:
A general active contour formulation is considered and a convexity
analysis of its energy function is presented. Conditions under which
this formulation has a unique solution are derived; these conditions
involve both the active contour energy potential and the regularization
parameters. This analysis is then applied to four particular active
contour formulations, revealing important characteristics about their
convexity, and suggesting that external potentials involving
center-of-mass computations may be better behaved than the usual
potentials based on image gradients. Our analysis also provides an
explanation for the poor convergence behavior at concave boundaries and
suggests an alternate algorithm for approaching these types of
boundaries. (C) 1999 Elsevier Science B.V. All rights reserved.
|
406. | Lee, MK, Drangova, M, Holdsworth, DW, and Fenster, A, "Application of dynamic computed tomography for measurements of local aortic elastic modulus," MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, vol. 37, pp. 13-24, 1999.
Abstract:
A novel computed tomographic (CT) technique used for the instantaneous
measurement of the dynamic elastic modulus of intact excised porcine
aortic vessels subjected to physiological pressure waveforms is
described. This system was comprised of a high resolution X-ray image
intensifier based computed tomographic system with limiting spatial
resolution of 3.2 mm(-1) (for a 40 mm field of view) and a
computer-controlled flow simulator. Utilising cardiac gating and
computer control, a time-resolved sequence of I mm thick axial
tomographic slices was obtained for porcine aortic specimens during one
simulated cardiac cycle. With an image acquisition sampling interval of
16.5 ms, the time sequences of CT slices were able to quantify the
expansion and contraction of the aortic wall during each phase of the
cardiac cycle. Through superficial tagging of the adventitial surface
of the specimens with wire markers, measurement of wall strain in
specific circumferential sectors and subsequent calculations of
localised dynamic elastic modulus were possible. The precision of
circumferential measurements made from the CT images utilising a
cluster-growing segmentation technique was approximately +/- 0.25 mm
and allowed determination of the dynamic elastic modulus (E-dyn) with a
precision of +/- 8 kPa. Dynamic elastic modulus was resolved as a
function of the harmonics of the physiological pressure waveform and as
a function of the angular position around the vessel circumference.
Application of this dynamic CT (DCT) technique to seven porcine
thoracic aortic specimens produced a circumferential average (over all
frequency components) E-dyn of 373 +/- 29 kPa. This value was not
statistically different (p < 0.05) from the values of 430 +/- 77 and
390 +/- 47 kPa obtained by uniaxial tensile testing and volumetric
measurements respectively.
|
407. | Yuen, PC, Feng, GC, and Zhou, JP, "A contour detection method: Initialization and contour model," PATTERN RECOGNITION LETTERS, vol. 20, pp. 141-148, 1999.
Abstract:
In this paper, a new contour detection method based on the snake model
is developed and reported. The proposed method consists of two steps.
The first step is to locate the initial snake contour and a novel
initialization algorithm has been developed. In the second step, an
improved snake algorithm is developed to locate the final contour(s).
Images with single and multiple objects are selected to evaluate the
capability of the proposed method and the results are encouraging. (C)
1999 Elsevier Science B.V. All rights reserved.
|
408. | Shareef, N, Wang, DL, and Yagel, R, "Segmentation of medical images using LEGION," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 74-91, 1999.
Abstract:
Advances in visualization technology and specialized graphic
workstations allow clinicians to virtually interact with anatomical
structures contained within sampled medical-image datasets, A hindrance
to the effective use of this technology is the difficult problem of
image segmentation. In this paper, we utilize a recently proposed
oscillator network called the locally excitatory globally inhibitory
oscillator network (LEGION) whose ability tb achieve fast synchrony
with local excitation and desynchrony with global inhibition makes it
an effective computational framework for grouping similar features and
segregating dissimilar ones in an image, We extract an algorithm from
LEGION dynamics and propose an adaptive scheme for grouping. We show
results of the algorithm to two-dimensional (2-D) and three-dimensional
(3-D) (volume) computerized topography (CT) and magnetic resonance
imaging (MRI) medical-image datasets, In addition, we compare our
algorithm with other algorithms for medical-image segmentation, as well
as with manual segmentation. LEGION's computational and architectural
properties make it a promising approach for real-time medical-image
segmentation.
|
409. | Conforti, D, and De Luca, L, "Computer implementation of a medical diagnosis problem by pattern classification," FUTURE GENERATION COMPUTER SYSTEMS, vol. 15, pp. 287-292, 1999.
Abstract:
In this paper we present a software system which can aid the medical
diagnostician for the diagnosis of breast cancers. The system has been
developed on a "Windows 95" platform and provides a user friendly
interface, made up of windows and visualization tools. An interesting
and innovative feature is represented by the telemedicine configuration
of the software system, which can be run in a remote fashion,
exploiting, from some remote regions, the expertize and the clinical
database available in advanced medical centers.
A prototype version of the software system, named CAMD (computer aided
medical diagnosis) is currently being tested and validated with the
collaboration of the Cytopathology Department of the Cosenza General
Hospital (Calabria, Italy). (C) 1999 Elsevier Science B.V. All rights
reserved.
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410. | Kervrann, C, and Heitz, F, "Statistical deformable model-based segmentation of image motion," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 8, pp. 583-588, 1999.
Abstract:
We present a statistical method for the motion-based segmentation of
deformable structures undergoing nonrigid movements. The proposed
approach relies on vivo models describing the shape of interest, its
variability, and its movement. The first model corresponds to a
statistical deformable template that constrains the shape and its
deformations. The second model is introduced to represent the optical
flow field inside the deformable template. These two models are
combined within a single probability distribution, which enables to
derive shape and motion estimates using a maximum likelihood approach.
The method requires no manual initialization and is demonstrated on
synthetic data and on a medical X-ray image sequence.
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411. | Casadei, S, and Mitter, S, "An efficient and provably correct algorithm for the multiscale estimation of image contours by means of polygonal lines," IEEE TRANSACTIONS ON INFORMATION THEORY, vol. 45, pp. 939-954, 1999.
Abstract:
A large portion of image contours is characterized by local properties
such as sharp variations of the image intensity across the contour, The
integration of local image descriptors estimated by using these local
properties into curvilinear descriptors is a difficult problem from a
theoretical viewpoint because of the combinatorially large number of
possible curvilinear descriptors. To deal with this difficulty, the
notion of compressible graphs is introduced and a contour data model is
defined leading to an efficient linear-time algorithm which provably
recovers contours with an upper bound on the approximation error.
|
412. | Yabuki, N, Matsuda, Y, Kimura, H, Fukui, Y, and Miki, S, "Region extraction using color feature and active net model in color image," IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, vol. E82A, pp. 466-472, 1999.
Abstract:
In this paper, we propose a method to detect a road sign from a road
scene image in the daytime. In order to utilize color feature of sign
efficiently, color distribution of sign is examined, and then color
similarity map is constructed. Additionally, color similarity shown on
the map is incorporated into image energy of an active net model. A
road sign is extracted as if it is wrapped up in an active net. Some
experimental results obtained by applying an active net to images are
presented.
|
413. | Sakaue, K, Amano, A, and Yokoya, N, "Optimisation approaches in computer vision and image processing," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E82D, pp. 534-547, 1999.
Abstract:
In this paper, the authors present general views of computer vision and
image processing based on optimization. Relaxation and regularization
in both broad and narrow senses are used in various fields and problems
of computer vision and image processing, and they are currently being
combined with general-purpose optimization algorithms. The principle
and case examples of relaxation and regularization are discussed; the
application of optimization to shape description that is a particularly
important problem in the field is described; and the use of a genetic
algorithm (GA) as a method of optimization is introduced.
|
414. | Berger, MO, Wrobel-Dautcourt, B, Petitjean, S, and Simon, G, "Mixing synthetic and video images of an outdoor urban environment," MACHINE VISION AND APPLICATIONS, vol. 11, pp. 145-159, 1999.
Abstract:
Mixing video and computer-generated images is a new and promising area
of research for enhancing reality. It can be used in all the situations
when a complete simulation would not be easy to implement. Past work on
the subject has relied for a large part on human intervention at key
moments of the composition. In this paper, we show that if enough
geometric information about the environment is available, then
efficient tools developed in the computer vision literature can be used
to build a highly automated augmented reality loop. We focus on outdoor
urban environments and present an application for the visual assessment
of a new lighting project of the bridges of Paris. We present a fully
augmented 300-image sequence of a specific bridge, the Pont Neuf
Emphasis is put on the robust calculation of the camera position. We
also detail the techniques used for matching 2D and 3D primitives and
for tracking features over the sequence. Our system overcomes two major
difficulties. First, it is capable of handling poor-quality images,
resulting from the fact that images were shot at night since the goal
was to simulate a new lighting system. Second, it can deal with
important changes in viewpoint position and in appearance along the
sequence. Throughout the paper, many results are shown to illustrate
the different steps and difficulties encountered.
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415. | Denzler, J, and Niemann, H, "Active rays: Polar-transformed active contours for real-time contour tracking," REAL-TIME IMAGING, vol. 5, pp. 203-213, 1999.
Abstract:
In this paper we describe a new approach to contour extraction and
tracking, which is based on the principles of active contour models and
overcomes its shortcomings. We formally introduce active rays, describe
the contour extraction as an energy minimization problem and discuss
what active contours and active rays have in common.
The main difference is that for active rays a unique ordering of the
contour elements in the 2D image plane is given,which cannot be found
for active contours. This is advantageous for predicting the contour
elements' position and prevents crossings in the contour. Furthermore,
another advantage is that instead of an energy minimization in the 2D
image plane the minimization is reduced to a 1D search problem. The
approach also shows any-time behavior, which is important with respect
to real-time applications. Finally, the method allows for the
management of multiple hypotheses of the object's boundary. This is an
important aspect if concave contours are to be tracked.
Results on real image sequences (tracking a toy train in a laboratory
scene, tracking pedestrians in an outdoor scene) show the suitability
of this approach for real-time object tracking in a closed loop between
image acquisition and camera movement. The contour tracking can be done
within the image frame rate (25 fps) on standard Unix workstations (HP
735) without any specialized hardware. (C) 1999 Academic Press.
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416. | Cotin, S, Delingette, H, and Ayache, N, "Real-time elastic deformations of soft tissues for surgery simulation," IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, vol. 5, pp. 62-73, 1999.
Abstract:
In this paper, we describe a new method for surgery simulation
including a volumetric model built from medical images and an elastic
modeling of the deformations. The physical model is based on elasticity
theory which suitably links the shape of deformable bodies and the
forces associated with the deformation. A real-time computation of the
deformation is possible thanks to a preprocessing of elementary
deformations derived from a finite element method. This method has been
implemented in a system including a force feedback device and a
collision detection algorithm. The simulator works in real-time with a
high resolution liver model.
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417. | Peckar, W, Schnorr, C, Rohr, K, and Stiehl, HS, "Parameter-free elastic deformation approach for 2D and 3D registration using prescribed displacements," JOURNAL OF MATHEMATICAL IMAGING AND VISION, vol. 10, pp. 143-162, 1999.
Abstract:
A parameter-free approach for non-rigid image registration based on
elasticity theory is presented. In contrast to traditional
physically-based numerical registration methods, no forces have to be
computed from image data to drive the elastic deformation. Instead,
displacements obtained with the help of mapping boundary structures in
the source and target image are incorporated as hard constraints into
elastic image deformation. As a consequence, our approach does not
contain any parameters of the deformation model such as elastic
constants. The approach guarantees the exact correspondence of boundary
structures in the images assuming that correct input data are
available. The implemented incremental method allows to cope with large
deformations. The theoretical background, the finite element
discretization of the elastic model, and experimental results for 2D
and 3D synthetic as well as real medical images are presented.
|
418. | Oztop, E, Mulayim, AY, Atalay, V, and Yarman-Vural, F, "Repulsive attractive network for baseline extraction on document images," SIGNAL PROCESSING, vol. 75, pp. 1-10, 1999.
Abstract:
This paper describes a new framework, called repulsive attractive (RA)
network for baseline extraction on document images. The RA network is
an energy minimizing dynamical system, which interacts with the
document text image through the attractive and repulsive forces defined
over the network components and the document image. Experimental
results indicate that the network can successfully extract the
baselines under heavy noise and overlaps between the ascending and
descending portions of the characters of adjacent lines. The proposed
framework is applicable to a wide range of image processing
applications, such as curve fitting, segmentation and thinning. (C)
1999 Elsevier Science B.V. All rights reserved.
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419. | Le Goualher, G, Procyk, E, Collins, DL, Venugopal, R, Barillot, C, and Evans, AC, "Automated extraction and variability analysis of sulcal neuroanatomy," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 206-217, 1999.
Abstract:
Systematic mapping of the variability in cortical sulcal anatomy is an
area of increasing interest which presents numerous methodological
challenges, To address these issues, we have implemented sulcal
extraction and assisted labeling (SEAL) to automatically extract the
two-dimensional (2-D) surface ribbons that represent the median axis of
cerebral sulci and to neuroanatomically label these entities,
To encode the extracted three-dimensional (3-D) cortical sulcal
schematic topography (CSST) we define a relational graph structure
composed of two main features: vertices (representing sulci) and arcs
(representing the relationships between sulci), Vertices contain a
parametric representation of the surface ribbon buried within the
sulcus, Points on this surface are expressed in stereotaxic coordinates
(i.e., with respect to a standardized brain coordinate system). For
each of these vertices, we store length, depth, and orientation as well
as anatomical attributes (e.g., hemisphere, lobe, sulcus type, etc.).
Each are stores the 3-D location of the junction between sulci as well
as a list of its connecting sulci,
Sulcal labeling is performed semiautomatically by selecting a sulcal
entity in the CSST and selecting from a menu of candidate sulcus names.
In order to help the user in the labeling task, the menu is restricted
to the most likely candidates by using priors for the expected sulcal
spatial distribution, These priors, i.e., sulcal probabilistic maps,
were created from the spatial distribution of 34 sulci traced manually
on 36 different subjects, Given these spatial probability maps, the
user is provided with the likelihood that the selected entity belongs
to a particular sulcus,
The cortical structure representation obtained by SEAL is suitable to
extract statistical information about both the spatial and the
structural composition of the cerebral cortical topography, This
methodology allows for the iterative construction of a successively
more complete statistical models of the cerebral topography containing
spatial distributions of the most important structures, their
morphometrics, and their structural components.
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420. | Gurcan, MN, Koyuturk, M, Yildiz, HS, Cetin-Atalay, R, and Cetin, AE, "Identification of relative protein bands in polyacrylamide gel electrophoresis (PAGE) using a multi-resolution snake algorithm," BIOTECHNIQUES, vol. 26, pp. 1162-+, 1999.
Abstract:
In polyacrylamide gel electrophoresis (PAGE) image analysis, it is
important to determine the percentage of the protein of interest of a
protein mixture. This study presents reliable computer software to
determine this percentage, The region of interest containing the
protein band is detected using the snake algorithm. The iterative snake
algorithm is implemented in a; multi-resolutional framework. The snake
is initialized on a low-resolution image. Then, the final position of
the snake at the low resolution is used as the initial position in the
higher-resolution image. Finally, the area of the protein is estimated
as the area enclosed by the final position of the snake.
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421. | Izquierdo, ME, "Disparity Segmentation analysis: Matching with an adaptive window and depth-driven segmentation," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol. 9, pp. 589-607, 1999.
Abstract:
Most of the emerging content-based multimedia technologies are based on
efficient methods to solve machine early vision tasks. Among others
tasks, object segmentation is perhaps the most important problem in
single image processing, whereas pixel-correspondence estimation is the
crucial task in multiview image analysis. The solution of these two
problems is the keg technology for the development of the majority of
leading-edge interactive video communication technologies and
telepresence systems. In this paper, we present a robust frame work
comprised of joined pixel-correspondence estimation and image
segmentation in video sequences taken simultaneously from different
perspectives. fin improved concept for stereo-image analysis based on
block matching with a local adaptive window is introduced. The size and
shape of the reference window is calculated adaptively according to the
degree of reliability of disparities estimated previously. Considerable
improvements are obtained just within object borders or image areas
that become occluded by applying the proposed block-matching model. An
initial object segmentation is obtained by merging neighboring sampling
positions with disparity vectors of similar size and direction.
Starting from this initial segmentation, true object borders are
detected using a contour-matching algorithm. In this process, the
contour of the initial segmentation is taken as a reference pattern,
and the edges extracted from the original images, by applying a
multiscale algorithm, are the candidates for the true object contour.
The performance of the introduced methods has been verified by computer
simulations using synthetic data and several natural stereo sequences.
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422. | Dougherty, L, Asmuth, JC, Blom, AS, Axel, L, and Kumar, R, "Validation of an optical flow method for tag displacement estimation," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 359-363, 1999.
Abstract:
We present a validation study of an optical-flow method for the rapid
estimation of myocardial displacement in magnetic resonance tagged
cardiac images. This registration and change visualization (RCV)
software uses a hierarchical estimation technique to compute the flow
field that describes the warping of an image of one cardiac phase into
alignment with the next. This method overcomes the requirement of
constant pixel intensity in standard optical-how methods by
preprocessing the input images to reduce any intensity bias which
results from the reduction in stripe contrast throughout the cardiac
cycle. To validate the method, SPAMM-tagged images were acquired of a
silicon gel phantom with simulated rotational motion. The pixel
displacement was estimated with the RCV method and the error in pixel
tracking was <4% 1000 ms after application of the tags, and after 30
degrees of rotation. An additional study was performed using a
SPAMM-tagged multiphase slice of a canine left ventricle. The true
displacement was determined using a previously validated active contour
model (snakes). The error between methods was 6.7% at end systole. The
RCV method has the advantage of tracking all pixels in the image in a
substantially shorter period than the snakes method.
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423. | Rettmann, ME, Xu, CY, Pham, DL, and Prince, JL, "Automated segmentation of sulcal regions," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, MICCAI'99, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1679, pp. 158-167, 1999.
Abstract:
Automatic segmentation and identification of cortical sulci play an
important role in the study of brain structure and function. In this
work, a method is presented for the automatic segmentation of sulcal
regions of cortex. Unlike previous methods that extract the sulcal
spaces within the cortex, the proposed method extracts actual regions
of the cortical surface that surround sulci. Sulcal regions are.
segmented from the medial surface as well as the lateral and inferior
surfaces. The method first generates a depth map on the surface,
computed by measuring the distance between the cortex and ail outer
"shrink-wrap" surface. Sulcal regions are then extracted using a
hierarchical algorithm that alternates between thresholding and region
growing operations. To visualize the buried regions of the segmented
cortical surface, ail efficient technique for mapping the surface to a
sphere is proposed. Preliminary results are presented on the geometric
analysis of sulcal regions for automated identification.
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424. | Frangi, AF, Niessen, WJ, Hoogeveen, RM, van Walsum, T, and Viergever, MA, "Quantitation of vessel morphology from 3D MRA," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, MICCAI'99, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1679, pp. 358-367, 1999.
Abstract:
Three dimensional magnetic resonance angiographic images (3D MRA) are
routinely inspected using maximum intensity projections (MIP). However,
accuracy of stenosis estimates based on projections is limited.
Therefore, a method for quantitative 3D MRA is introduced. Linear
vessel segments are modeled with a central vessel axis curve coupled to
a vessel wall surface. First, the central vessel axis is determined.
Subsequently, the vessel wall is segmented using knowledge of the
acquisition process. The user interaction to initialize the model is
performed in a 3D setting. The method is validated on a carotid
bifurcation phantom and also illustrated on patient data.
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425. | Guo, YL, and Vemuri, BC, "Hybrid geometric active models for shape recovery in medical images," INFORMATION PROCESSING IN MEDICAL IMAGING, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1613, pp. 112-125, 1999.
Abstract:
In this paper, we propose extensions to a powerful geometric shape
modeling scheme introduced in [14]. The extension allows the model to
automatically cope with topological changes and for the first time,
introduces the concept of a global shape into geometric/geodesic snake
models. The ability to characterize global shape of an object using
very few parameters facilitates shape learning and recognition. In this
new modeling scheme, object shapes are represented using a
parameterized function - called the generator - which accounts for the
global shape of an object and the pedal curve/surface of this global
shape with respect to a geometric snake to represent any local detail.
Traditionally, pedal curves/surfaces are defined as the loci of the
feet of perpendiculars to the tangents of the generator from a fixed
point called the pedal point. We introduce physics-based control for
shaping these geometric models by using distinct pedal points - lying
on a snake - for each point on the generator. The model dubbed as a
"snake pedal" allows for interactive manipulation via forces applied to
the snake. Automatic topological changes of the model may be achieved
by implementing the geometric active contour in a level-set framework.
We demonstrate the applicability of this modeling scheme via examples
of shape estimation from a variety of medical image data.
|
426. | Frangi, AF, Niessen, WJ, Hoogeveen, RM, van Walsum, T, and Viergever, MA, "Model-based quantitation of 3-D magnetic resonance angiographic images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 946-956, 1999.
Abstract:
Quantification of the degree of stenosis or vessel dimensions are
important for diagnosis of vascular diseases and planning vascular
interventions, Although diagnosis from three-dimensional (3-D) magnetic
resonance angiograms (MRA's) is mainly performed on two-dimensional
(2-D) maximum intensity projections, automated quantification of
vascular segments directly from the 3-D dataset is desirable to provide
accurate and objective measurements of the 3-D anatomy.
A model-based method for quantitative 3-D MRA is proposed. Linear
vessel segments are modeled with a central vessel axis curve coupled to
a vessel wall surface. A novel image feature to guide the deformation
of the central vessel axis is introduced. Subsequently, concepts of
deformable models are combined with knowledge of the physics of the
acquisition technique to accurately segment the vessel wall and compute
the vessel diameter and other geometrical properties.
The method is illustrated and validated on a carotid bifurcation
phantom, with ground truth and medical experts as comparisons, Also,
results on 3-D time-of-flight (TOF) MRA images of the carotids are
shown, The approach is a promising technique to assess several
geometrical vascular parameters directly on the source 3-D images,
providing an objective mechanism for stenosis grading.
|
427. | Toyama, K, and Hager, GD, "Incremental focus of attention for robust vision-based tracking," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 35, pp. 45-63, 1999.
Abstract:
We present the Incremental Focus of Attention (IFA) architecture for
robust, adaptive, real-time motion tracking. IFA systems combine
several visual search and vision-based tracking algorithms into a
layered hierarchy. The architecture controls the transitions between
layers and executes algorithms appropriate to the visual environment at
hand: When conditions are good, tracking is accurate and precise; as
conditions deteriorate, more robust, yet less accurate algorithms take
over; when tracking is lost altogether, layers cooperate to perform a
rapid search for the target and continue tracking.
Implemented IFA systems are extremely robust to most common types of
temporary visual disturbances. They resist minor visual perturbances
and recover quickly after full occlusions, illumination changes, major
distractions, and target disappearances. Analysis of the algorithm's
recovery times are supported by simulation results and experiments on
real data. In particular, examples show that recovery times after lost
tracking depend primarily on the number of objects visually similar to
the target in the field of view.
|
428. | Ladret, P, Latombe, B, and Granada, F, "Active contour algorithm: An attractive tool for snow avalanche analysis," SIGNAL PROCESSING, vol. 79, pp. 197-204, 1999.
Abstract:
Image processing is increasingly used for the study of snow avalanches
in order to prevent them. The study of the dynamics of snow avalanches
has produced many numerical models. The difficulty of the measurement
of parameters provided by these models has prevented their validation
by comparison with those of real phenomena. Image processing is a first
approach for these validations. This study aims to determine and
analyse the velocity of the envelope in case of powder-snow avalanches.
This work is based on active snake methods. In this paper, we present a
new algorithm of active contours in order to analyse the front of
motion of snow avalanches. The algorithm uses an energy-minimising
curve. The model developed takes avalanche characteristics and the
nature of the images into account. The algorithm gives good results and
we obtain a sequence of avalanche contours. (C) 1999 Elsevier Science
B.V. All rights reserved.
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429. | Unser, M, "Splines - A perfect fit for signal and image processing," IEEE SIGNAL PROCESSING MAGAZINE, vol. 16, pp. 22-38, 1999.
Abstract:
Image processing is increasingly used for the study of snow avalanches
in order to prevent them. The study of the dynamics of snow avalanches
has produced many numerical models. The difficulty of the measurement
of parameters provided by these models has prevented their validation
by comparison with those of real phenomena. Image processing is a first
approach for these validations. This study aims to determine and
analyse the velocity of the envelope in case of powder-snow avalanches.
This work is based on active snake methods. In this paper, we present a
new algorithm of active contours in order to analyse the front of
motion of snow avalanches. The algorithm uses an energy-minimising
curve. The model developed takes avalanche characteristics and the
nature of the images into account. The algorithm gives good results and
we obtain a sequence of avalanche contours. (C) 1999 Elsevier Science
B.V. All rights reserved.
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430. | Xu, XY, Long, Q, Collins, MW, Bourne, M, and Griffith, TM, "Reconstruction of blood flow patterns in human arteries," PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE, vol. 213, pp. 411-421, 1999.
Abstract:
Local haemodynamic factors in large arteries are associated with the
pathophysiology of cardiovascular diseases such as atherosclerosis and
strokes. In search of these factors and their correlation with atheroma
formation, quantitative haemodynamic data in realistic arterial
geometry become crucial. At present no in vivo non-invasive technique
is available that can provide accurate measurement of three-dimensional
blood velocities and shear stresses in curved and branching sites of
vessels where atherosclerotic plaques are found frequently. This paper
presents a computer modelling technique which combines state-of-the-art
computational fluid dynamics (CFD) with new noninvasive magnetic
resonance imaging techniques to provide the complete haemodynamic data
in 'real' arterial geometries. Using magnetic resonance angiographic
and velocity images acquired from the aortic bifurcation of a healthy
human subject, CFD simulations have been carried out and the predicted
flow patterns demonstrate the non-planar-type flow characteristics
found in experimental studies.
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431. | Aubert, G, and Blanc-Feraud, L, "Some remarks on the equivalence between 2D and 3D classical snakes and geodesic active contours," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 34, pp. 19-28, 1999.
Abstract:
Recently, Caselles et al. have shown the equivalence between a
classical snake problem of Kass et al. and a geodesic active contour
model. The PDE derived from the geodesic problem gives an evolution
equation for active contours which is very powerfull for image
segmentation since changes of topology are allowed using the level set
implementation. However in Caselles' paper the equivalence with
classical snake is only shown for 2D images and 1D curves, by using
concepts of Hamiltonian theory which have no meanings for active
surfaces. This paper propose to examine the notion of equivalence and
to revisite Caselles et al. arguments. Then a notion equivalence is
introduced and shown for classical snakes and geodesic active contours
in the 2D (active contour) and 3D (active surface) case.
|
432. | Salden, AH, Romeny, BMT, and Viergever, MA, "Linearised euclidean shortening flow of curve geometry," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 34, pp. 29-67, 1999.
Abstract:
The geometry of a space curve is described in terms of a Euclidean
invariant frame field, metric, connection, torsion and curvature. Here
the torsion and curvature of the connection quantify the curve
geometry. In order to retain a stable and reproducible description of
that geometry, such that it is slightly affected by non-uniform
protrusions of the curve, a linearised Euclidean shortening flow is
proposed. (Semi)-discretised versions of the flow subsequently
physically realise a concise and exact (semi-)discrete curve geometry.
Imposing special ordering relations the torsion and curvature in the
curve geometry can be retrieved on a multi-scale basis not only for
simply closed planar curves but also for open, branching, intersecting
and space curves of non-trivial knot type. In the context of the
shortening flows we revisit the maximum principle, the semi-group
property and the comparison principle normally required in scale-space
theories. We show that our linearised flow satisfies an adapted maximum
principle, and that its Green's functions possess a semi-group
property. We argue that the comparison principle in the case of knots
can obstruct topological changes being in contradiction with the
required curve simplification principle. Our linearised flow paradigm
is not hampered by this drawback; all non-symmetric knots tend to
trivial ones being infinitely small circles in a plane. Finally, the
differential and integral geometry of the multi-scale representation of
the curve geometry under the flow is quantified by endowing the
scale-space of curves with an appropriate connection, and calculating
related torsion and curvature aspects. This multi-scale modern
geometric analysis forms therewith an alternative for curve description
methods based on entropy scale-space theories.
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433. | Weerasinghe, C, Yan, H, and Ji, LL, "A fast method for estimation of object rotation function in MRI using a similarity criterion among k-space overlap data," SIGNAL PROCESSING, vol. 78, pp. 215-230, 1999.
Abstract:
A major obstacle to the success of post-processing artifact correction
techniques in magnetic resonance imaging (MRI) is the scarcity of
reliable motion estimation algorithms. Most on-line motion estimation
schemes demand patient preparation, modifications to standard spin-echo
pulse sequences and increased scanning times. Therefore, off-line
motion estimation algorithms have gained interest in the research
arena. However, the existing algorithms are plagued by high
computational and time demands that restrict the estimation capability
to only a few motion parameters. This paper presents an efficient
off-line motion estimation algorithm with applications to in-plane
rotational motion artifact correction in MRI. The algorithm is based on
maximizing the similarity among the k-space data subjected to angular
overlap. The initial guesses are derived from measuring projection
width of X-directional inverse Fourier transforms of the acquired
k-space views. Simulation studies involving stepwise and continuous
rotation show that the proposed method can accurately estimate rotation
angles corresponding to each view. This method has been incorporated in
a rotational motion artifact correction scheme, previously developed by
the authors, producing successful results. (C) 1999 Elsevier Science
B.V. All rights reserved.
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434. | Aletras, AH, Balaban, RS, and Wen, H, "High-resolution strain analysis of the human heart with fast-DENSE," JOURNAL OF MAGNETIC RESONANCE, vol. 140, pp. 41-57, 1999.
Abstract:
Single breath-hold displacement data from the human heart were acquired
with fast-DENSE (fast displacement encoding with stimulated echoes)
during systolic contraction at 2.5 x 2.5 mm in-plane resolution.
Encoding strengths of 0.86-1.60 mm/pi were utilized in order to extend
the dynamic range of the phase measurements and minimize effects of
physiologic and instrument noise. The noise level in strain
measurements for both contraction and dilation corresponded to a strain
value of 2.8%. In the human heart, strain analysis has sufficient
resolution to reveal transmural variation across the left ventricular
wall. Data processing required minimal user intervention and provided a
rapid quantitative feedback. The intrinsic temporal integration of
fast-DENSE achieves high accuracy at the expense of temporal resolution.
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435. | Cagnoni, S, Dobrzeniecki, AB, Poli, R, and Yanch, JC, "Genetic algorithm-based interactive segmentation of 3D medical images," IMAGE AND VISION COMPUTING, vol. 17, pp. 881-895, 1999.
Abstract:
This article describes a method for evolving adaptive procedures for
the contour-based segmentation of anatomical structures in 3D medical
data sets. With this method, the user first manually traces one or more
2D contours of an anatomical structure of interest on parallel planes
arbitrarily cutting the data set. Such contours are then used as
training tramples for a genetic algorithm to evolve a contour detector.
By applying the detector to the rest of the image sequence it is
possible to obtain a full segmentation of the structure. The same
detector can then be used to segment other image sequences of the same
sort. Segmentation is driven by a contour-tracking strategy that relies
on an elastic-contour model whose parameters are also optimized by the
genetic algorithm. We report results obtained on a software-generated
phantom and on real tomographic images of different sorts. (C) 1999
Elsevier Science B.V. All rights reserved.
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436. | Sakalli, M, Yan, H, and Fu, A, "A region-based scheme using RKLT and predictive classified vector quantization," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 75, pp. 269-280, 1999.
Abstract:
This paper proposes a compression scheme for face profile images based
on three stages, modelling, transformation, and the partially
predictive classified vector quantization (CVQ) stage. The modelling
stage employs deformable templates in the localisation of salient
features of face images and in the normalization of the image content.
The second stage uses a dictionary of feature-bases trained for profile
face images to diagonalize the image blocks. At this stage, all
normalized training and test images are spatially clustered
(objectively) into four subregions according to their energy content,
and the residuals of the most important clusters are further clustered
(subjectively) in the spectral domain, to exploit spectral
redundancies. The feature-basis functions are established with the
region-based Karhunen-Loeve transform (RKLT) of clustered image blocks.
Each image block is matched with a representative of near-best basis
functions. A predictive approach is employed for mid-energy clusters,
in both stages of search for a basis and for a codeword from the range
of its cluster. The proposed scheme employs one stage of a cascaded
region-based KLT-SVD and CVQ complex, followed by residual VQ stages
for subjectively important regions. The first dictionary of
feature-bases is dedicated to the main content of the image and the
second is dedicated to the residuals. The proposed scheme is
experimented in a set of human face images. (C) 1999 Academic Press.
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437. | Astrom, K, Cipolla, R, and Giblin, P, "Generalised epipolar constraints," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 33, pp. 51-72, 1999.
Abstract:
In this paper we will discuss structure and motion problems for curved
surfaces. These will be studied using the silhouettes or apparent
contours in the images. The problem of determining camera motion from
the apparent contours of curved three-dimensional surfaces, is studied.
It will be shown how special points, called epipolar tangency points or
frontier points, can be used to solve this problem. A generalised
epipolar constraint is introduced, which applies to points, curves, as
well as to apparent contours of surfaces. The theory is developed for
both continuous and discrete motion, known and unknown orientation,
calibrated and uncalibrated, perspective, weak perspective and
orthographic cameras. Results of an iterative scheme to recover the
epipolar line structure from real image sequences using only the
outlines of curved surfaces, is presented. A statistical evaluation is
performed to estimate the stability of the solution. It is also shown
how the motion of the camera from a sequence of images can be obtained
from the relative motion between image pairs.
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438. | Xu, CY, Pham, DL, Rettmann, ME, Yu, DN, and Prince, JL, "Reconstruction of the human cerebral cortex from magnetic resonance images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 467-480, 1999.
Abstract:
Reconstructing the geometry of the human cerebral cortex from MR images
is an important step in both brain mapping and surgical path planning
applications, Difficulties with imaging noise, partial volume
averaging, image intensity inhomogeneities, convoluted cortical
structures, and the requirement to preserve anatomical topology make
the development of accurate automated algorithms particularly
challenging. In this paper ne address each of these problems and
describe a systematic method for obtaining a surface representation of
the geometric central layer of the human cerebral cortex. Using fuzzy
segmentation, an isosurface algorithm, and a deformable surface model,
the method reconstructs the entire cortex with the correct topology,
including deep convoluted sulci and gyri. The method is largely
automated and its results are robust to imaging noise, partial volume
averaging, and image intensity inhomogeneities. The performance of this
method is demonstrated, both qualitatively and quantitatively and the
results of its application to sis subjects and one simulated MR brain
volume are presented.
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439. | Lee, JD, "Wavelet transform for 3-D reconstruction from series sectional medical images," MATHEMATICAL AND COMPUTER MODELLING, vol. 30, pp. 1-13, 1999.
Abstract:
It is well known that the 3-D shape of an organ can be reconstructed
from a series of cross-sectional images of human body using ultrasound,
Computer Topography (CT), or Magnetic Resonance Imaging (MRI). From the
reconstructed images, qualitative evaluation, quantitative analysis,
and other further clinical research become possible. In this paper, a
novel interpolation technique that utilizes the whole object contour
information and with no need of feature matching for object
reconstruction is proposed. In the method, multiresolution analysis of
the object contour of each slices is carried out by using the Wavelet
Transformation (WT). The primary contour of the interslices is
reconstructed from the coarsest scale information of the slices, while
the refined contours are estimated by taking into account the lower
scale information of slices. To evaluate the performance of the
proposed method and the traditional method, a performance measure is
proposed and the experimental results are also included, (C) 1999
Elsevier Science Ltd. All rights reserved.
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440. | Knoll, C, Alcaniz, M, Grau, V, Monserrat, C, and Juan, MC, "Outlining of the prostate using snakes with shape restrictions based on the wavelet transform (Doctoral Thesis: Dissertation)," PATTERN RECOGNITION, vol. 32, pp. 1767-1781, 1999.
Abstract:
This paper considers the problem of deformable contour initialization
and modeling for segmentation of the human prostate in medical images.
We propose a new technique for elastic deformation restriction to
particular object shapes of any closed planar curve using localized
multiscale contour parameterization based on the 1D dyadic wavelet
transform. For this purpose we define internal curve deformation forces
as a result of multiscale parametrical contour analysis. The form
restricted contour deformation and its initialization by template
matching are performed in a coarse to fine segmentation process based
on a multiscale image edge representation containing the important
edges of the image at various scales. The method is useful for 3D
conformal radiotherapy planning and automatic prostate volume
measurements in ultrasonographic diagnosis. (C) 1999 Pattern
Recognition Society. Published by Elsevier Science Ltd. All rights
reserved.
|
441. | Huang, WC, Hsu, CC, Lee, C, and Lai, PH, "Recurrent nasal tumor detection by dynamic MRI," IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, vol. 18, pp. 100-105, 1999.
Abstract:
This paper considers the problem of deformable contour initialization
and modeling for segmentation of the human prostate in medical images.
We propose a new technique for elastic deformation restriction to
particular object shapes of any closed planar curve using localized
multiscale contour parameterization based on the 1D dyadic wavelet
transform. For this purpose we define internal curve deformation forces
as a result of multiscale parametrical contour analysis. The form
restricted contour deformation and its initialization by template
matching are performed in a coarse to fine segmentation process based
on a multiscale image edge representation containing the important
edges of the image at various scales. The method is useful for 3D
conformal radiotherapy planning and automatic prostate volume
measurements in ultrasonographic diagnosis. (C) 1999 Pattern
Recognition Society. Published by Elsevier Science Ltd. All rights
reserved.
|
442. | Kozerke, S, Botnar, R, Oyre, S, Scheidegger, MB, Pedersen, EM, and Boesiger, P, "Automatic vessel segmentation using active contours in cine phase contrast flow measurements," JMRI-JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 10, pp. 41-51, 1999.
Abstract:
The segmentation of images obtained by cine magnetic resonance (MR)
phase contrast velocity mapping using manual or semi-automated methods
is a time consuming and observer-dependent process that still hampers
the use of now quantification in a clinical setting. A fully automatic
segmentation method based on active contour model algorithms for
defining vessel boundaries has been developed, For segmentation, the
phase image, in addition to the magnitude image, is used to address
image distortions frequently seen in the magnitude image of disturbed
now fields. A modified definition for the active contour model is
introduced to reduce the influence of missing or spurious edge
information of the vessel wall. The method was evaluated on now phantom
data and on in vivo images acquired in the ascending aorta of humans.
Phantom experiments resulted in an error of 0.8% in assessing the
luminal area of a now phantom equipped with an artificial heart valve.
Blinded evaluation of the volume now rates from automatic vs. manual
segmentation of gradient echo (FFE) phase contrast images obtained in
vivo resulted in a mean difference of -0.9 +/- 3%. The mean difference
from automatic vs. manual segmentation of images acquired with a hybrid
phase contrast sequence (TFEPI) within a single breath-hold was -0.9
+/- 6%. J. Magn. Reson. Imaging 1999: 10:41-51. (C) 1999 Wiley-Liss,
Inc.
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443. | Zhao, BS, Yankelevitz, D, Reeves, A, and Henschke, C, "Two-dimensional multi-criterion segmentation of pulmonary nodules on helical CT images," MEDICAL PHYSICS, vol. 26, pp. 889-895, 1999.
Abstract:
A multi-criterion algorithm for automatic delineation of small
pulmonary nodules on helical CT images has been developed. In a
slice-by-slice manner, the algorithm uses density, gradient strength,
and a shape constraint of the nodule to automatically control
segmentation process. The multiple criteria applied to separation of
the nodule from its surrounding structures in lung are based on the
fact that typical small pulmonary nodules on CT images have high
densities, show a distinct difference in density at the boundary, and
tend to be compact in shape. Prior to the segmentation, a
region-of-interest containing the nodule is manually selected on the CT
images. Then the segmentation process begins with a high density
threshold that is decreased stepwise, resulting in expansion of the
area of nodule candidates. This progressive region growing approach is
terminated when subsequent thresholds provide either a diminished
gradient strength of the nodule contour or significant changes of
nodule shape :from the compact form. The shape criterion added to the
algorithm can effectively prevent the high density surrounding
structures (e.g., blood vessels) from being falsely segmented as
nodule, which occurs frequently when only the gradient strength
criterion is applied. This has been demonstrated by examples given in
the Results section. The algorithm's accuracy has been compared with
that of radiologist's manual segmentation, and no statistically
significant difference has been found between the nodule areas
delineated by radiologist and those obtained by the multi-criterion
algorithm. The improved nodule boundary allows for more accurate
assessment of nodule size and hence nodule growth over a short time
period, and for better characterization of nodule edges. This
information is useful in determining malignancy status of a nodule at
an early stage and thus provides significant guidance for further
clinical management. (C) 1999 American Association of Physicists in
Medicine.
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444. | Levienaise-Obadia, B, and Gee, A, "Adaptive segmentation of ultrasound images," IMAGE AND VISION COMPUTING, vol. 17, pp. 583-588, 1999.
Abstract:
This article describes a novel approach to the semi-automatic
segmentation of ultrasound images. Assisted segmentation is
particularly attractive when processing many slices through a 3D data
set, and even though fully automatic segmentation would be ideal, this
is currently not feasible given the quality of ultrasound images. The
algorithm developed in this article is based on the active contour
paradigm, with several important modifications. The contour is
attracted to boundaries described locally by statistical models: this
allows for the fact that the definition of what constitutes a boundary
may vary around the boundary's length. The statistical models are
trained on-the-fly by observing boundaries accepted by the operator. In
this way, operator intervention in a particular slice is sensibly
exploited to reduce the need for intervention in subsequent slices. The
resulting algorithm provides fast, reliable and verifiable segmentation
of in vivo ultrasound images. (C) 1999 Elsevier Science B.V. All rights
reserved.
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445. | Peterfreund, N, "Robust tracking of position and velocity with Kalman snakes," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 21, pp. 564-569, 1999.
Abstract:
A new Kalman-filter based active contour model is proposed for tracking
of nonrigid objects in combined spatio-velocity space. The model
employs measurements of gradient-based image potential and of
optical-flow along the contour as system measurements. In order to
improve robustness to image clutter and to occlusions an optical-flow
based detection mechanism is proposed. The method detects and rejects
spurious measurements which are not consistent with previous estimation
of image motion.
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446. | Mayer, H, "Automatic object extraction from aerial imagery - A survey focusing on buildings," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 74, pp. 138-149, 1999.
Abstract:
This paper surveys the state-of-the-art automatic object extraction
techniques from aerial imagery. It focuses on building extraction
approaches, which present the majority of the work in this area. After
proposing well-defined criteria for their assessment, characteristic
approaches are selected and assessed, based on their models and
strategies. The assessment gives rise to a combined model and strategy
covering the current knowledge in the field. The model comprises: the
derivation of characteristic properties from the function of objects;
three-dimensional geometry and material properties; scales and levels
of abstraction/aggregation; local and global context. The strategy
consists of grouping, focusing on different scales, context-based
control and generation of evidence from structures of parts, and fusion
of data and algorithms. Many ideas which have not been explored in
depth lead to promising directions for further research. (C) 1999
Academic Press.
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447. | Malassiotis, S, and Strintzis, MG, "Tracking the left ventricle in echocardiographic images by learning heart dynamics," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 18, pp. 282-290, 1999.
Abstract:
In this paper a temporal learning-filtering procedure is applied to
refine the left ventricle (LV) boundary detected by an active-contour
model. Instead of making prior assumptions about the LV shape or its
motion, this information is incrementally gathered directly from the
images and is exploited to achieve more coherent segmentation, A Hough
transform technique is used to find an initial approximation of the
object boundary at the first frame of the sequence, Then, an
active-contour model is used in a coarse-to-fine framework, for the
estimation of a noisy LV boundary, The PCA transform is applied to form
a reduced ordered orthonormal basis of the LV deformations based on a
sequence of noisy boundary observations. Then this basis is used to
constrain the motion of the active contour in subsequent frames, and
thus provide more coherent identification. Results of epicardial
boundary identification in E-mode images are presented.
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448. | Udupa, JK, "Three-dimensional visualization and analysis methodologies: A current perspective," RADIOGRAPHICS, vol. 19, pp. 783-806, 1999.
Abstract:
Three-dimensional (3D) imaging was developed to provide both
qualitative and quantitative information about an object or object
system from images obtained with multiple modalities including digital
radiography, computed tomography, magnetic resonance imaging, positron
emission tomography, single photon emission computed tomography, and
ultrasonography, Three-dimensional imaging operations may be classified
under four basic headings: preprocessing, visualization, manipulation,
and analysis. Preprocessing operations (volume of interest, filtering,
interpolation, registration, segmentation) are aimed at extracting or
improving the extraction of object information in given images.
Visualization operations facilitate seeing and comprehending objects in
their full dimensionality and may be either scene-based or
object-based. Manipulation may be either rigid or deformable acid
allows alteration of object structures and of relationships between
objects. Analysis operations, like visualization operations, may be
either scene-based or object-based and deal with methods of quantifying
object information. There are many challenges involving matters of
precision, accuracy, and efficiency in 3D imaging. Nevertheless, 3D
imaging is an exciting technology that promises to offer an expanding
number and variety of applications.
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449. | Kuijer, JPA, Marcus, JT, Gotte, MJW, van Rossum, AC, and Heethaar, RM, "Simultaneous MRI tagging and through-plane velocity quantification: A three-dimensional myocardial motion tracking algorithm," JMRI-JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 9, pp. 409-419, 1999.
Abstract:
A tracking algorithm was developed for calculation of three-dimensional
point-specific myocardial motion. The algorithm was designed for images
acquired with simultaneous magnetic resonance imaging (MRI) grid
tagging and through-plane velocity quantification. The tagging grid
provided the in-plane motion while the velocity quantification measured
the through-plane motion, In four healthy volunteers, the in vivo
performance was evaluated by comparing the systolic through-plane
displacement with the displacement of tagging-grid intersections in
long-axis images, The correlation coefficient was 0.93 (P < 0.001, N =
183), A t-test for paired samples revealed a small underestimation of
the through-plane displacement by 0.04 +/- 0.09 cm (mean +/- SD, P <
0.001) on an average displacement of 0.77 +/- 0.23 cm toward the apex.
The authors conclude that three-dimensional point-specific motion
tracking based on simultaneous tagging and velocity quantification is
competitive with other methods such as tagging in mutually orthogonal
image planes or quantification of three orthogonal velocity components,
(C) 1999 Wiley-Liss, Inc.
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450. | Shufelt, JA, "Performance evaluation and analysis of monocular building extraction from aerial imagery," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 21, pp. 311-326, 1999.
Abstract:
Research in monocular building extraction from aerial imagery has
neglected performance evaluation in three areas: unbiased metrics for
quantifying detection and delineation performance, an evaluation
methodology for applying these metrics to a representative body of test
imagery, and an approach for understanding the impact of image and
scene content on building extraction algorithms. This paper addresses
these areas with an end-to-end performance evaluation of four existing
monocular building extraction systems, using image space and object
space-based metrics on 83 test images of 18 sites. This analysis is
supplemented by an examination of the effects of image obliquity and
object complexity on system performance, as well as a case study on the
effects of edge fragmentation. This widely applicable performance
evaluation approach highlights the consequences of various traditional
assumptions about camera geometry, image content, and scene structure,
and demonstrates the utility of rigorous photogrammetric object space
modeling and primitive-based representations for building extraction.
|
451. | Schnabel, JA, and Arridge, SR, "Active shape focusing," IMAGE AND VISION COMPUTING, vol. 17, pp. 419-428, 1999.
Abstract:
This paper presents a framework for hierarchical shape description
which enables quantitative and qualitative shape studies at multiple
levels of image detail. It allows the capture of the global object
shape at higher image scales, and to focus it down to finer details at
decreasing levels of image scale. A multi-scale active contour model,
whose energy function is regularized with respect to underlying
geometric image structure in a natural scale setting, is developed for
the purpose of implicit shape extraction or regularization with respect
to scale. The resulting set of shapes is formulated and visualized as a
multi-scale shape stack for the investigation of shape changes across
scales. We demonstrate the functionality of this framework by applying
it to a set of true fractal structures, and to 3D brain MRI. The
framework is shown to be capable of recovering the fractal dimension of
the fractal shapes directly from their embedding image context. The
equivalent measure on the medical images and its potential for medical
shape analysis is discussed. (C) 1999 Elsevier Science B.V. All rights
reserved.
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452. | Morris, DT, and Donnison, C, "Identifying the neuroretinal rim boundary using dynamic contours," IMAGE AND VISION COMPUTING, vol. 17, pp. 169-174, 1999.
Abstract:
The neuroretinal rim forms the outer boundary of the optic nerve head:
that region of the retina where blood vessels and nerve fibres pass out
of the eye. It is normally a circular structure, but is known to change
shape due to nerve damage in glaucoma. Its shape can therefore be used
in the diagnosis and assessment of the treatment of this disease.
Automatically finding the boundary would be useful as it would allow
reliable quantitative shape measurements to be made. However, it is a
difficult problem as the boundary is ill defined and partially obscured
by blood vessels. In this paper we present an algorithm that
successfully identifies the boundary using dynamic contours (snakes).
The success of the algorithm is very dependent on preprocessing the
image to enhance the contrast between the retina and the optic nerve
head. We therefore describe the preprocessing in some detail. The
algorithm has been tested on numerous images and found to be
successful, as judged by an optometrist, in every case. (C) 1999
Elsevier Science B.V. All rights reserved.
|
453. | Horritt, MS, "A statistical active contour model for SAR image segmentation," IMAGE AND VISION COMPUTING, vol. 17, pp. 213-224, 1999.
Abstract:
A statistical active contour model is developed for segmenting
synthetic aperture radar (SAR) images into regions of homogeneous
speckle statistics. The technique measures both the local tone and
texture along the contour so that no smoothing across segment
boundaries occurs. A smooth contour is favoured by the inclusion of a
curvature constraint, whose weight is determined analytically by
considering the model energy balance. The algorithm spawns smaller
snakes to represent multiply connected regions. The algorithm is
capable of segmenting noisy SAR imagery whilst accurately depicting (to
within 1 pixel) segment boundaries. (C) 1999 Elsevier Science B.V. All
rights reserved.
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2000 |
454. | Araabi, BN, Kehtarnavaz, N, McKinney, T, Hillman, G, and Wursig, B, "A string matching computer-assisted system for dolphin photoidentification," ANNALS OF BIOMEDICAL ENGINEERING, vol. 28, pp. 1269-1279, 2000.
Abstract:
This paper presents a syntactic/semantic string representation scheme
as well as a string matching method as part of a computer-assisted
system to identify dolphins from photographs of their dorsal fins. A
low-level string representation is constructed from the curvature
function of a dolphin's fin trailing edge, consisting of positive and
negative curvature primitives. A high-level string representation is
then built over the low-level string via merging appropriate groupings
of primitives in order to have a less sensitive representation to
curvature fluctuations or noise. A family of syntactic/semantic
distance measures between two strings is introduced. A composite
distance measure is then defined and used as a dissimilarity measure
for database search, highlighting both the syntax (structure or
sequence) and semantic (attribute or feature) differences. The syntax
consists of an ordered sequence of significant protrusions and
intrusions on the edge, while the semantics consist of seven attributes
extracted from the edge and its curvature function-The matching results
are reported for a database of 624 images corresponding to 164
individual dolphins. The identification results indicate that the
developed string matching method performs better than the previous
matching methods including dorsal ratio, curvature, and curve matching.
The developed computer-assisted system can help marine mammalogists in
their identification of dolphins, since it allows them to examine only
a handful of candidate images instead of the currently used manual
searching of the entire database. (C) 2000 Biomedical Engineering
Society. [S0090-6964(00)00510-5].
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455. | Froumentin, M, Labrosse, F, and Willis, P, "A vector-based representation for image warping," COMPUTER GRAPHICS FORUM, vol. 19, pp. C419-+, 2000.
Abstract:
A method for image analysis, representation and re-synthesis is
introduced. Unlike other schemes it is not pixel based but rather
represents a picture as vector data, from which an altered version of
the original image can be rendered. Representing an image as vector
data allows performing operations such as zooming, retouching or
colourising, avoiding common problems associated with pixel image
manipulation.
This paper brings together methods from the areas of computer vision,
image compositing and image based rendering to prove that this type of
image representation is a step towards accurate and efficient image
manipulation.
|
456. | Sarti, A, de Solorzano, CO, Lockett, S, and Malladi, R, "A geometric model for 3-D confocal image analysis," IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 47, pp. 1600-1609, 2000.
Abstract:
In this paper, we use partial-differential-equation-based filtering as
a preprocessing add post processing strategy for computer-aided
cytology, We wish to accurately extract and classify. the shapes of
nuclei from confocal microscopy images, which is a prerequisite to an
accurate quantitative intranuclear (genotypic and phenotypic) and
internuclear (tissue structure) analysis of tissue and cultured
specimens. First, we study the use of a geometry-driven edge-preserving
image smoothing mechanism before nuclear segmentation. We show how this
biter outperforms other widely-used filters in that it provides higher
edge fidelity. Then we apply the same filter,,vith a different initial
condition, to smooth nuclear surfaces and obtain sub-pixel accuracy.
Finally we use another instance of the geometrical filter to correct
for misinterpretations of the nuclear surface by the segmentation
algorithm. Our prefiltering and post filtering nicely complements our
initial segmentation strategy, in that it provides substantial and
measurable improvement in the definition of the nuclear surfaces.
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457. | Fu, Y, Erdem, AT, and Tekalp, AM, "Tracking visible boundary of objects using occlusion adaptive motion snake," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 2051-2060, 2000.
Abstract:
We propose a novel technique for tracking the visible boundary of a
video object in the presence of occlusion, Starting with an initial
contour that is interactively specified by the user and may be
automatically refined by using intraenergy terms, the proposed
technique employs piecewise contour prediction using local motion and
color information on both sides of the contour segment, and contour
snapping using scale-invariant intraframe and interframe energy terms.
The piecewise (segmented) nature of the contour prediction scheme and
modeling of the motion on both sides of each contour segment enable
accurate determination of whether and where the tracked boundary is
occluded by another object. The proposed snake energy terms are
associated with contour segments (as opposed to node points) and they
are scale/resolution independent to allow multi-resolution contour
tracking without the need to retune the weights of the energy terms at
each resolution level. This facilitates contour prediction at coarse
resolution and snapping at fine resolution with high accuracy.
Experimental results are provided to illustrate the performance of the
proposed occlusion detection algorithm and the novel snake energy terms
that enable visible boundary tracking in the presence of occlusion.
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458. | Vanegas, O, Tokuda, K, and Kitamura, T, "Lip location normalized training for visual speech recognition," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E83D, pp. 1969-1977, 2000.
Abstract:
This paper describes a method to normalize the lip position for
improving the performance of a visual-information-based speech
recognition system. Basically, there are two types of information
useful in speech recognition processes; the first one is the speech
signal itself and the second one is the visual information from the
lips in motion. This paper tries to solve some problems caused by using
images from the lips in motion such as the effect produced by the
Variation of the lip location. The proposed lip location normalization
method is based on a search algorithm of the lip position in which the
location normalization is integrated into the model training.
Experiments of speaker-independent isolated word recognition were
carried out on the Tulips1 and M2VTS databases. Experiments showed a
recognition rate of 74.5% and an error reduction rate of 35.7% for the
ten digits word recognition M2VTS database.
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459. | Furukawa, T, Gu, J, Lee, WS, and Magnenat-Thalmann, N, "3D clothes modeling from photo cloned human body," VIRTUAL WORLDS, LECTURE NOTES IN ARTIFICIAL INTELLIGENCE, vol. 1834, pp. 159-170, 2000.
Abstract:
An important advantage of virtual reality technology is that real 3D
objects including humans can be edited in the virtual world. In this
paper, we present a technique for 3D clothes modeling based on a photo
cloned human body. Photo cloning is an efficient 3D human body modeling
method using a generic body model and photographs. A part segmentation
technique for 3D color objects is applied for the clothes modeling,
which uses multi-dimensional mixture Gaussians fitting. Firstly, we
construct a 6D point set representing both the geometric and color
information Next, the mixture Gaussians are fitted to the point set by
using the EM algorithm in order to determine the clusters. This
approximation gives probabilities for each point. Finally the
probabilities determine the segmented part models corresponding to the
clothes models. An advantage of this method is that the clustering is
unsupervised learning without any prior knowledge as well as
integrating geometric and color data in multi-dimensional space.
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460. | Ding, ZH, and Friedman, MH, "Quantification of 3-D coronary arterial motion using clinical biplane cineangiograms," INTERNATIONAL JOURNAL OF CARDIAC IMAGING, vol. 16, pp. 331-346, 2000.
Abstract:
Speculation that the motion of the coronary arteries might be involved
in the pathogenesis of coronary atherosclerosis has generated growing
interest in the study of this motion. Accordingly, a system has been
developed to quantify 3-D coronary arterial motion using clinical
biplane cineangiograms. Exploiting the temporal continuity of
sequential angiographic images, a template matching technique is
designed to track the non-uniform frame-to-frame motion of coronary
arteries without assuming that the vessels experience uniform axial
strain. The implementation of the system is automated by a
coarse-to-fine matching process, thus improving the efficiency and
objectivity of motion analysis. The system has been validated and
employed to characterize the in vivo motion dynamics of human coronary
arteries; illustrative results show that this system is a promising
tool for routine clinical and laboratory analysis of coronary arterial
motion.
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461. | Wu, RY, Ling, KV, and Ng, WS, "Automatic prostate boundary recognition in sonographic images using feature model and genetic algorithm," JOURNAL OF ULTRASOUND IN MEDICINE, vol. 19, pp. 771-782, 2000.
Abstract:
This paper describes the development of a model based boundary
recognition system for transrectal prostate ultrasonographic images. It
consists of two techniques: boundary modeling and boundary searching
with model constraints. To achieve higher specificity of the model, a
method called feature modeling is derived from the existing point
distribution modeling method. To improve the robustness of the
searching technique, the genetic algorithm is used. Incremental genetic
algorithm with crowding replacement and binary string chromosome type
was found experimentally to give good search results. It was shown that
the system could recognize the boundary with considerable accuracy and
consistency within a few minutes in transrectal ultrasonographic images
taken from approximate middle position of the prostate.
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462. | Leavers, VF, "Use of the two-dimensional Radon Transform to generate a taxonomy of shape for the characterization of abrasive powder particles," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 1411-1423, 2000.
Abstract:
A novel image processing technique for the extraction of parameters
characteristic of the shape and angularity of abrasive powder particles
is proposed. The image data are not analyzed directly. Information
concerning angularity and shape is extracted from the parametric
transformation of the 2D binarized edge map. The transformation process
used, the Radon Transform, is one to many, that is, each image point
generates in transform space the parameters of all the possible curves
on which it may lie and the resulting distribution is an accumulation
of that evidence. Once the image data are segmented, the technique has
the potential to deliver a comprehensive numerical description of the
shape and angularity of the particles under investigation without the
need for further interaction by the operator. The parameters obtained
are arranged into a Taxonomy according to their usefulness in
categorizing the shapes under inspection. The technique is novel in
that it offers an analytical definition of a corner and its apex and it
automatically selects only those protrusions coincident with the convex
hull of the shape and, hence, those most likely to contribute to the
process of abrasion. The advantages and potential pitfalls of using the
technique are illustrated and discussed using real image data.
|
463. | Chen, CM, and Lu, HHS, "An adaptive snake model for ultrasound image segmentation: Modified trimmed mean filter, ramp integration and adaptive weighting parameters," ULTRASONIC IMAGING, vol. 22, pp. 214-236, 2000.
Abstract:
The snake model is a widely-used approach to finding the boundary of
the object of interest in an ultrasound image. However, due to the
speckles, the weak edges and the tissue-related textures in an
ultrasound image, conventional snake models usually cannot obtain the
desired boundary satisfactorily. In this paper, we propose a new
adaptive snake model for ultrasound image segmentation. The proposed
snake model is composed of three major techniques, namely, the modified
trimmed mean (MTM) filtering, ramp integration and adaptive weighting
parameters. With the advantages of the mean and median filters, the MIM
filter is employed to alleviate the speckle interference in the
segmentation process. The weak edge enhancement by ramp integration
attempts to capture the slowly varying edges, which are hard to capture
by conventional snake models. The adaptive weighting parameter allows
weighting of each energy term to change adaptively during the
deformation process. The proposed snake model has been verified on the
phantom and clinical ultrasound images. The experimental results showed
that the proposed snake model achieves a reasonable performance with an
initial contour placed 10 to 20 pixels away from the desired boundary.
The mean minimal distances from the derived boundary to the desired
boundary have been shown to be less than 3.5 (for CNR greater than or
equal to 0.5) and 2.5 pixels, respectively, for the phantom and
ultrasound images.
|
464. | Zaritsky, R, Peterfreund, N, and Shimkin, N, "Velocity-Guided tracking of deformable contours in three dimensional space," COMPUTER VISION - ECCV 2000, PT I, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1842, pp. 251-266, 2000.
Abstract:
This paper presents a 3D active contour model for boundary tracking,
motion analysis and position prediction of non-rigid objects, which
applies stereo vision and velocity control to the class of deformable
contour models, known as snakes. The proposed contour evolves in three
dimensional space in reaction to a 3D potential function, which is
derived by projecting the contour onto the 2D stereo images. The
potential function is augmented by a velocity term, which is related to
the three dimensional velocity field along the contour, and is used to
guide the contour displacement between subsequent images. This leads to
improved spatio-temporal tracking performance, which is demonstrated
through experimental results with real and synthetic images. Good
tracking performance is obtained with as little as one iteration per
frame, which provides a considerable advantage for real time operation.
|
465. | Harari, D, Furst, M, Kiryati, N, Caspi, A, and Davidson, M, "Computer-based assessment of body image distortion in anorexia nervosa patients," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 766-775, 2000.
Abstract:
A computer-based method for the assessment of body image distortions in
anorexia nervosa and other eating-disordered patients is presented. At
the core of the method is a realistic pictorial simulation of lifelike
weight-changes, applied to a real source image of the patient. The
patients, using a graphical user interface, adjust their body shapes
until they meet their self-perceived appearance. Measuring the extent
of virtual fattening or slimming of a body with respect to its real
shape and size, allows direct, quantitative evaluation of the cognitive
distortion in body image. In a preliminary experiment involving 20
anorexia-nervosa patients, 70% of the subjects chose an image with
simulated visual weight gain of about 20% as their "real" body image.
None of them recognized the original body image, thus demonstrating the
quality of the transformed images. The method presented can be applied
in the research, diagnosis, evaluation and treatment of eating
disorders.
|
466. | Baert, SAM, Niessen, WJ, Meijering, EHW, Frangi, AF, and Viergever, MA, "Guide wire tracking during endovascular interventions," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 727-734, 2000.
Abstract:
A method is presented to extract and track the position of a guide wire
during endovascular interventions under X-ray fluoroscopy. The method
can be used to improve guide wire visualization in the low quality
fluoroscopy images. A two-step procedure is utilized to track the guide
wire in subsequent frames. First a rough estimate of the displacement
is obtained using a template matching procedure. Subsequently, the
position of the guide wire is determined by fitting the guide wire to a
feature image in which line-like structures are enhanced. In this
optimization step the influence of the scale at which the feature is
calculated and the additional value of using directional information is
investigated. The method is applied both on the original and
subtraction images. Using the proper parameter settings, the guide wire
could successfully be tracked based on the original images, in 141 out
of 146 frames from 5 image sequences.
|
467. | Jang, DS, Jang, SW, and Choi, HI, "Structured Kalman filter for tracking partially occluded moving objects," BIOLOGICALLY MOTIVATED COMPUTER VISION, PROCEEDING, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1811, pp. 248-257, 2000.
Abstract:
Moving object tracking is one of the most important techniques in
motion analysis and understanding, and it has many difficult problems
to solve. Especially estimating and tracking moving objects, when the
background and moving objects vary dynamically, are very difficult. The
Kalman filter has been used to estimate motion information and use the
information in predicting the appearance of targets in succeeding
frames. It is possible under such a complex environment that targets
may disappear totally or partially due to occlusion by other objects.
In this paper, we propose another version of the Kalman filter, to be
called Structured Kalman filter, which can successfully work its role
of estimating motion information under such a deteriorating condition
as occlusion. Experimental results allow that the suggested approach is
very effective in estimating and tracking non-rigid moving objects
reliably.
|
468. | Gatzoulis, L, Anderson, T, Pye, SD, O'Donnell, R, McLean, CC, and McDicken, WN, "Scanning techniques for three-dimensional forward-viewing intravascular ultrasound imaging," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 26, pp. 1461-1474, 2000.
Abstract:
Intravascular ultrasound (US) imaging is a useful tool for assessing
arterial disease and aiding treatment procedures. Forward-viewing
intravascular US imaging could be of particular use in severely
stenosed or totally occluded arteries, where the current side-viewing
intravascular US systems are limited by their inability to access the
site of interest. In this study, five 3-D forward-viewing intravascular
scanning patterns were investigated. The work was carried out using
scaled-up vessel phantoms constructed from tissue-mimicking material
and a PC-controlled scanning and acquisition system. The scanning
patterns were examined and evaluated with regard to the image quality
of dense and sparse data sets, the accuracy of quantitative
measurements of lumen dimensions and the potential for clinical use.
The relative merits and drawbacks of the different patterns are
discussed and a preferred scanning pattern is recommended. (C) 2001
World Federation for Ultrasound in Medicine & Biology.
|
469. | Murino, V, and Trucco, A, "Three-dimensional image generation and processing in underwater acoustic vision," PROCEEDINGS OF THE IEEE, vol. 88, pp. 1903-1946, 2000.
Abstract:
Underwater exploration is becoming more and more important for many
applications involving physical, biological, geological,
archaeological, and industrial issues. Unfortunately, only a small
percentage of potential resources has been exploited under the sea. The
inherent structureless environment and the difficulties implied by the
nature of the propagating medium have placed limitations on the sensing
and the understanding of the underwater world. Typically, acoustic
imaging systems are widely utilized for both large- and small-scale
underwater investigations, as they can more easily achieve short and
large visibility ranges, though at the expense of a coarse resolution
and a poor visual quality.
This paper aims at surveying the up-to-date advances in acoustic
acquisition systems and data processing techniques, especially focusing
on three-dimensional (3-D) short-range imaging for scene reconstruction
and understanding. In fact, the advent of smarter and more efficient
imaging systems has allowed the generation of good-quality
high-resolution images and the related design of proper techniques for
underwater scene understanding. The term acoustic vision is introduced
to generally describe all data processing (especially image processing)
methods devoted to the interpretation of a scene. Since acoustics is
also used for medical applications, a short overview of the related
systems for biomedical acoustic image formation is provided.
The final goal of the paper is to establish the state of the art of the
techniques and algorithms for acoustic image generation and processing,
providing technical details and results for the most promising
techniques, and pointing out the potential capabilities of this
technology for underwater scene understanding.
|
470. | Zeng, ZH, and Ma, SD, "Real-time face tracking under partial occlusion and illumination change," ADVANCES IN MULTIMODAL INTERFACES - ICMI 2000, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1948, pp. 135-142, 2000.
Abstract:
In this paper, we present an approach which tracks human faces robustly
in real-time applications by taking advantage of both region matching
and active contour model. Region matching with motion prediction
robustly locates the approximate position of the target, then active
contour model detects the local variation of the target's boundary
which is insensitive to illumination changes, and results from active
contour model guides updating the template for successive tracking. In
this case, the system can tolerate changes in both pose and
illumination. To reduce the influence of local error due to partial
occlusion and weak edge strength, we use a priori knowledge of head
shape to re-initialize the curve of the object every a few frames. To
realize real-time tracking, we adopt region matching with adaptively
matching density and modify greedy algorithm to be more effective in
its implementation. The proposed technique is applied to track the head
of the person who is doing Taiji exercise in live video sequences. The
system demonstrates promising performance, and the tracking time per
frame is about 40ms on Pentium II 400MHZ PC.
|
471. | Wang, R, Gao, W, and Ma, JY, "An approach to robust and fast locating lip motion," ADVANCES IN MULTIMODAL INTERFACES - ICMI 2000, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1948, pp. 332-339, 2000.
Abstract:
In this paper,we present a novel approach to robust and fast locating
lip motion.Firstly, the fisher transform with constraints is presented
to enhance the lip region in a face image. Secondly, two distribution
characteristics of the lip in human face space are proposed to increase
the accuracy and and real-time implementation performance of lip
locating Experiments with 2000 images show that this approach can
satisfy requirements not only in real-time performance but also in
reliability and accuracy.
|
472. | Tabb, K, Davey, N, Adams, R, and George, S, "Analysis of human motion using snakes and neural networks," ARTICULATED MOTION AND DEFORMABLE OBJECTS, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1899, pp. 48-57, 2000.
Abstract:
A novel technique is described for analysing human movement in outdoor
scenes. Following initial detection of the humans using active contour
models, the contours are then re-represented as normalised axis
crossover vectors. These vectors are then fed into a neural network
which determines the typicality of a given human shape, allowing for a
given human's motion deformation to be analysed. Experiments are
described which investigate the success of the technique being
presented.
|
473. | Schenk, A, Prause, G, and Peitgen, HO, "Efficient semiautomatic segmentation of 3D objects in medical images," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 186-195, 2000.
Abstract:
We present a fast and accurate tool for semiautomatic segmentation of
volumetric medical images based on the live wire algorithm, shape-based
interpolation and a new optimization method.
While the user-steered live wire algorithm represents an efficient,
precise and reproducible method for interactive segmentation of
selected two-dimensional images, the shape-based interpolation allows
the automatic approximation of contours on slices between user-defined
boundaries. The combination of both methods leads to accurate
segmentations with significantly reduced user interaction time.
Moreover, the subsequent automated optimization of the interpolated
object contours results in a better segmentation quality or can be used
to extend the distances between user-segmented images and for a further
reduction of interaction time, Experiments were carried out on hepatic
computer tomographies from three different clinics. The results of the
segmentation of liver parenchyma have shown that the user interaction
time can be reduced more than 60% by the combination of shape-based
interpolation and our optimization method with volume deviations in the
magnitude of inter-user differences.
|
474. | Chen, T, and Metaxas, D, "Image segmentation based on the integration of Markov Random Fields and deformable models," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 256-265, 2000.
Abstract:
This paper proposes a new methodology for image segmentation based on
the integration of deformable and Markov Random Field models. Our
method makes use of Markov Random Field theory to build a Gibbs Prior
model of medical images with arbitrary initial parameters to estimate
the boundary of organs with low signal to noise ratio (SNR). Then we
use a deformable model to fit the estimated boundary, The result of the
deformable model fit is used to update the Gibbs prior model
parameters, such as the gradient threshold of a boundary. Based on the
updated parameters we restart the Gibbs prior models. By iteratively
integrating these processes we achieve an automated segmentation of the
initial images. By careful choice of the method used for the Gibbs
prior models, and based on the above method of integration with
deformable model our segmentation solution runs in close to real time.
Results of the method are presented for several examples, including
some MRI images with significant amount of noise.
|
475. | Moretti, B, Fadili, JM, Ruan, S, Bloyet, D, and Mazoyer, B, "Phantom-based performance evaluation: Application to brain segmentation from magnetic resonance images," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 303-316, 2000.
Abstract:
This paper presents a new technique for assessing the accuracy of
segmentation algorithms, applied to the performance evaluation of brain
editing and brain tissue segmentation algorithms for magnetic resonance
images. We propose performance evaluation criteria derived from the use
of the realistic digital brain phantom Brainweb. This 'ground truth'
allows us to build distance-based discrepancy features between the
edited brain or the segmented brain tissues (such as cerebro-spinal
fluid, grey matter and white matter) and the phantom model, taken as a
reference. Furthermore, segmentation errors can be spatially
determined, and ranged in terms of their distance to the reference. The
brain editing method used is the combination of two segmentation
techniques. The first is based on binary mathematical morphology and a
region growing approach. It represents the initialization step, the
results of which are then refined with the second method, using an
active contour model. The brain tissue segmentation used is based on a
Markov random field model. Segmentation results are shown on the
phantom for each method, and on real magnetic resonance images for the
editing step; performance is evaluated by the new distance-based
technique and corroborates the effective refinement of the segmentation
using active contours. The criteria described here can supersede biased
Visual inspection in order to compare, evaluate and validate any
segmentation algorithm. Moreover, provided a 'ground truth' is given,
we are able to determine quantitatively to what extent a segmentation
algorithm is sensitive to internal parameters, noise, artefacts or
distortions. (C) 2000 Elsevier Science B.V. All rights reserved.
|
476. | Rifai, H, Bloch, I, Hutchinson, S, Wiart, J, and Garnero, L, "Segmentation of the skull in MRI volumes using and taking the partial volume effect into account deformable model," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 219-233, 2000.
Abstract:
Segmentation of the skull in medical imagery is an important stage in
applications that require the construction of realistic models of the
head. Such models are used, for example, to simulate the behavior of
electro-magnetic fields in the head and to model the electrical
activity of the cortex in EEG and MEG data. in this paper, we present a
new approach for segmenting regions of bone in MRI volumes using
deformable models. Our method takes into account the partial volume
effects that occur with MRI data, thus permitting a precise
segmentation of these bone regions. At each iteration of the
propagation of the model, partial volume is estimated in a narrow band
around the deformable model, Our segmentation method begins with a
pre-segmentation stage, in which a preliminary segmentation of the
skull is constructed using a region-growing method. The surface that
bounds the pre-segmented skull region offers an automatic 3D
initialization of the deformable model. This surface is then propagated
(in 3D) in the direction of its normal. This propagation is achieved
using level set method, thus permitting changes to occur in the
topology of the surface as it evolves, an essential capability for our
problem. The speed at which the surface evolves is a function of the
estimated partial volume. This provides a sub-voxel accuracy in the
resulting segmentation. (C) 2000 Elsevier Science B.V. All rights
reserved.
|
477. | Westin, CF, Richolt, J, Moharir, V, and Kikinis, R, "Affine adaptive filtering of CT data," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 161-177, 2000.
Abstract:
A novel method for resampling and enhancing image data using
multidimensional adaptive fillers is presented. The underlying issue
that this paper addresses is segmentation of image structures that are
close in size to the voxel geometry. Adaptive filtering is used to
reduce both the effects of partial volume averaging by resampling the
data to a lattice with higher sample density and to reduce the image
noise level. Resampling is achieved by constructing filter sets that
have subpixel offsets relative to the original sampling lattice. The
filters are also frequency corrected for ansisotropic voxel dimensions.
The shift and the voxel dimensions are described by an affine transform
and provides a model for tuning the filter frequency functions. The
method has been evaluated on CT data where the voxels are in general
non cubic. The in-plane resolution in CT image volumes is often higher
by a factor of 3-10 than the through-plane resolution. The method
clearly shows an improvement over conventional resampling techniques
such as cubic spline interpolation and sine interpolation. (C) 2000
Elsevier Science B.V. All rights reserved.
|
478. | Ozanian, TO, and Phillips, R, "Image analysis for computer-assisted internal fixation of hip fractures," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 137-159, 2000.
Abstract:
This paper focuses on the task of automatic feature detection for
intra-operative drilling trajectory planning for computer-assisted
internal fixation of hip fractures. The features of interest are the
lateral cortex line of the femoral shaft, the femoral neck centre and
the femoral head centre, the latter being the most challenging of all.
Since the object is known, the detection process is regarded as a
localisation task rather than a recognition one. Simple anatomical
relationships between bone parts provide a naturally hierarchical
approach to searching, allowing refinement of image-derived information
based on a priori constraints. Use of knowledge and an unconventional
"divide-and-conquer" approach produce more reliable and faster results
than the standard global image processing routine. Analysis of summed
1D grey level profiles is used as a main segmentation tool to carry out
the above strategy. (C) 2000 Elsevier Science B.V. All rights reserved.
|
479. | McInerney, T, and Terzopoulos, D, "T-snakes: Topology adaptive snakes," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 73-91, 2000.
Abstract:
We present a new class of deformable contours (snakes) and apply them
to the segmentation of medical images. Our snakes are defined in terms
of an affine cell image decomposition (ACID). The 'snakes in ACID'
framework significantly extends conventional snakes, enabling
topological flexibility among other features. The resulting topology
adaptive snakes, or 'T-snakes', can be used to segment some of the most
complex-shaped biological structures from medical images in an
efficient and highly automated manner. (C) 2000 Elsevier Science BN.
All rights reserved.
|
480. | Westin, CF, Lorigo, LM, Faugeras, O, Grimson, WEL, Dawson, S, Norbash, A, and Kikinis, R, "Segmentation by adaptive geodesic active contours," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 266-275, 2000.
Abstract:
This paper introduces the use of spatially adaptive components into the
geodesic active contour segmentation method for application to
volumetric medical images. These components are derived from local
structure descriptors and are used both in regularization of the
segmentation and in stabilization of the image-based vector field which
attracts the contours to anatomical structures in the images. They are
further used to incorporate prior knowledge about spatial location of
the structures of interest. These components can potentially decrease
the sensitivity to parameter settings inside the contour evolution
system while increasing robustness to image noise. We show segmentation
results on blood vessels in magnetic resonance angiography data and
bone in computed tomography data.
|
481. | Boykov, Y, and Jolly, MP, "Interactive organ segmentation using graph cuts," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 276-286, 2000.
Abstract:
An N-dimensional image is divided into "object" and "background"
segments using a graph cut approach, A graph is formed by connecting
all pairs of neighboring image pixels (voxels) by weighted edges.
Certain pixels (voxels) have to be a priori identified as object or
background seeds providing necessary clues about the image content. Our
objective is to find the cheapest way to cut the edges in the graph so
that the object seeds are completely separated from the background
seeds. If the edge cost is a decreasing function of the local intensity
gradient then the minimum cost cut should produce an object/background
segmentation with compact boundaries along the high intensity gradient
values in the image. An efficient, globally optimal solution is
possible via standard min-cut/max-flow algorithms for graphs with two
terminals. We applied this technique to interactively segment organs in
various 2D and 3D medical images.
|
482. | Yao, JH, and Taylor, R, "Tetrahedral mesh modeling of density data for anatomical atlases and intensity-based registration," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 531-540, 2000.
Abstract:
In this paper, we present the first phase of our effort to build a bone
density atlas. We adopted a tetrahedral mesh structure to represent
anatomical structures. We propose an efficient and automatic algorithm
to construct the tetrahedral mesh from contours in CT images
corresponding to the outer bone surfaces and boundaries between compact
bone, spongy bone, and medullary cavity. We approximate bone density
variations by means of continuous density functions in each tetrahedron
of the mesh. Currently, our density functions are second degree
polynomial functions expressed in terms of barycentric coordinates
associated with each tetrahedron. We apply our density model to
efficiently generate Digitally Reconstructed Radiographs. These results
are immediately applicable as means of speeding up 2D-3D and 3D-3D
intensity based registration and will be incorporated into our future
work on construction of atlases and deformable intensity-based
registration.
|
483. | Hernandez-Hoyos, M, Anwander, A, Orkisz, M, Roux, JP, Douek, P, and Magnin, IE, "A deformable vessel model with single point initialization for segmentation, quantification and visualization of blood vessels in 3D MRA," MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1935, pp. 735-745, 2000.
Abstract:
We deal with image segmentation applied to three-dimensional (3D)
analysis of of vascular morphology in magnetic resonance angiography
(MRA) images. The main goal of our work is to develop a fast and
reliable method for stenosis quantification. The first step towards
this purpose is the extraction of the vessel axis by an expansible
skeleton method. Vessel boundaries are then detected in the planes
locally orthogonal to the centerline using an improved active contour.
Finally, area measurements based on the resulting contours allow the
calculation of stenosis parameters. The expansible nature of the
skeleton associated with a single point initialization of the active
contour allows overcoming some limitations of traditional deformable
models. As a result, the algorithm performs well even for severe
stenosis and significant vessel curvatures. Experimental results are
presented in 3D phantom images as well as in real images of patients.
|
484. | Gomes, J, and Faugeras, O, "Level sets and distance functions," COMPUTER VISION - ECCV 2000, PT I, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1842, pp. 588-602, 2000.
Abstract:
This paper is concerned with the simulation of the Partial Differential
Equation (PDE) driven evolution of a closed surface by means of an
implicit representation. In most applications, the natural choice for
the implicit representation is the signed distance function to the
closed surface. Osher and Sethian propose to evolve the distance
function with a Hamilton-Jacobi equation. Unfortunately the solution to
this equation is not a distance function. As a consequence, the
practical application of the level set method is plagued with such
questions as when do we have to "reinitialize" the distance function?
How do we "reinitialize" the distance function? Etc... which reveal a
disagreement between the theory and its implementation. This paper
proposes an alternative to the use of Hamilton-Jacobi equations which
eliminates this contradiction: in our method the implicit
representation always remains a distance function by construction, and
the implementation does not differ from the theory anymore. This is
achieved through the introduction of a new equation. Besides its
theoretical advantages, the proposed method also has several practical
advantages which we demonstrate in three applications: (i) the
segmentation of the human cortex surfaces from MRI images using two
coupled surfaces [27], (ii) the construction of a hierarchy of
Euclidean skeletons of a 3D surface, (iii) the reconstruction of the
surface of 3D objects through stereo [13].
|
485. | Weerasinghe, C, Ji, L, and Yan, H, "A new method for ROI extraction from motion affected MR images based on suppression of artifacts in the image background," SIGNAL PROCESSING, vol. 80, pp. 867-881, 2000.
Abstract:
Patient motion during a magnetic resonance imaging (MRI) examination
causes ghost artifacts and blurring in the image. Object boundary
extraction from such a degraded image is a challenging task, especially
if the motion function of the object is unknown. Although there are
many algorithms presently available for solving segmentation tasks,
they can be easily misled by the ghost artifacts and blurring in the
background of the image. Therefore, we propose a two-step background
clearing algorithm, in order to facilitate the object boundary
extraction. The first step involves selection of the least motion
affected views, using an entropy minimization criterion for suppression
of motion induced blur. The second step involves cancellation of the
remaining ghost artifacts, using a fuzzy model representing the image
background region. Both the steps involved in background clearing tend
to increase the number of dark pixels in the image. The contour
extraction is performed using an active contour model (snake), which
was previously developed by the authors. The proposed method has been
applied to phantom data affected by severe rotational motion and to
spin-echo MR images, producing encouraging results. (C) 2000 Elsevier
Science B.V. All rights reserved.
|
486. | Tsap, LV, Goldgof, DB, Sarkar, S, and Powers, PS, "A method for increasing precision and reliability of elasticity analysis in complicated burn scar cases," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 14, pp. 189-210, 2000.
Abstract:
In this paper we propose a method for increasing precision and
reliability of elasticity analysis in complicated burn scar cases. The
need for a technique that would help physicians by objectively
assessing elastic properties of scars, motivated our original
algorithm. This algorithm successfully employed active contours for
tracking and finite element models for strain analysis. However, the
previous approach considered only one normal area and one abnormal area
within the region of interest, and scar shapes which were somewhat
simplified. Most burn scars have rather complicated shapes and may
include multiple regions with different elastic properties. Hence, we
need a method capable of adequately addressing these characteristics.
The new method can split the region into more than two localities with
different material properties, select and quantify abnormal areas, and
apply different forces if it is necessary for a better shape
description of the scar.
The method also demonstrates the application of scale and mesh
refinement techniques in this important domain. It is accomplished by
increasing the number of Finite Element Method (FEM) areas as well as
the number of elements within the area. The method is successfully
applied to elastic materials and real burn scar cases. We demonstrate
all of the proposed techniques and investigate the behavior of
elasticity function in a 3-D space. Recovered properties of elastic
materials are compared with those obtained by a conventional
mechanics-based approach. Scar ratings achieved with the method are
correlated against the judgments of physicians.
|
487. | Jang, DS, and Choi, HI, "Active models for tracking moving objects," PATTERN RECOGNITION, vol. 33, pp. 1135-1146, 2000.
Abstract:
In this paper, we propose a model-based tracking algorithm which can
extract trajectory information of a target object by detecting and
tracking a moving object from a sequence of images. The algorithm
constructs a model from the detected moving object and match the model
with successive image frames to track the target object. We use an
active model which characterizes regional and structural features of a
target object such as shape, texture, color, and edgeness. Our active
model can adapt itself dynamically to an image sequence so that it can
track a non-rigid moving object. Such an adaptation is made under the
framework of energy minimization. We design an energy function so that
the Function can embody structural attributes of a target as well as
its spectral attributes. We applied Kalman filter to predict motion
information, The predicted motion information by Kalman filter was used
very efficiently to reduce the search space in the matching process,
(C) 2000 Pattern Recognition Society. Published by Elsevier Science
Ltd. All rights reserved.
|
488. | Bronkorsta, PJH, Reinders, MJT, Hendriks, EA, Grimbergen, J, Heethaar, RM, and Brankenhoff, GJ, "On-line detection of red blood cell shape using deformable templates," PATTERN RECOGNITION LETTERS, vol. 21, pp. 413-424, 2000.
Abstract:
For the purpose of automating a clinical diagnostic apparatus to
quantify the deformability of human red blood cells, we present an
automated image analysis procedure for on-line detection of the cell
shape based upon the method of parametric deformable templates. (C)
2000 Elsevier Science B.V. All rights reserved.
|
489. | Lanterman, AD, Grenander, U, and Miller, MI, "Bayesian segmentation via asymptotic partition functions," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 337-347, 2000.
Abstract:
Asymptotic approximations to the partition function of Gaussian random
fields are derived. Textures are characterized via Gaussian random
fields induced by stochastic difference equations determined by
finitely supported, stationary, linear difference operators, adjusted
to be nonstationary at the boundaries. It is shown that as the scale of
the underlying shape increases, the log-normalizer converges to the
integral of the log-spectrum of the operator inducing the random field.
Fitting the covariance of the fields amounts to fitting the parameters
of the spectrum of the differential operator-induced random field
model. Matrix analysis techniques are proposed for handling textures
with variable orientation. Examples of texture parameters estimated
from training data via asymptotic maximum-likelihood are shown.
Isotropic models involving powers of the Laplacian and directional
models involving partial derivative mixtures are explored. Parameters
are estimated for mitochondria and actin-myocin complexes in electron
micrographs and clutter in forward-looking infrared images. Deformable
template models are used to infer the shape of mitochondria in electron
micrographs, with the asymptotic approximation allowing easy
recomputation of the partition function as inference proceeds.
|
490. | Gomes, J, and Faugeras, O, "Reconciling distance functions and level sets," JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, vol. 11, pp. 209-223, 2000.
Abstract:
This paper is concerned with the simulation of the partial differential
equation driven evolution of a closed surface by means of an implicit
representation. In most applications, the natural choice for the
implicit representation is the signed distance function to the closed
surface. Osher and Sethian have proposed to evolve the distance
function with a Hamilton-Jacobi equation. Unfortunately the solution to
this equation is not a distance function. As a consequence, the
practical application of the level set method is plagued with such
questions as When do we have to reinitialize the distance function? How
do we reinitialize the distance function?, which reveal a disagreement
between the theory and its implementation. This paper proposes an
alternative to the use of Hamilton-Jacobi equations which eliminates
this contradiction: in our method the implicit representation always
remains a distance function by construction, and the implementation
does not differ from the theory anymore. This is achieved through the
introduction of a new equation. Besides its theoretical advantages, the
proposed method also has several practical advantages which we
demonstrate in three applications: (i) the segmentation of the human
cortex surfaces from MRI images using two coupled surfaces (X. Zeng, et
al., in Proceedings of the International Conference on Computer Vision
and Pattern Recognition, June 1998), (ii) the construction of a
hierarchy of Euclidean skeletons of a 3D surface, (iii) the
reconstruction of the surface of 3D objects through stereo (O. Faugeras
and R. Keriven, Lecture Notes in Computer Science, Vol. 1252, pp.
272-283). (C) 2000 Academic Press.
|
491. | Shah, J, "Riemannian drums, anisotropic curve evolution, and segmentation," JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, vol. 11, pp. 142-153, 2000.
Abstract:
The method of curve evolution is a popular method for recovering shape
boundaries. However, isotropic metrics have always been used to induce
the how of the curve and potential steady states tend to be difficult
to determine numerically, especially in noisy or tow-contrast
situations. Initial curves shrink past the steady slate and soon
vanish. In this paper, anisotropic metrics are considered to remedy the
situation by taking the orientation of the feature gradient into
account. The problem of shape recovery or segmentation is formulated as
the problem of finding minimum cuts of a Riemannian manifold.
Approximate methods, namely anisotropic geodesic flows and the solution
of an eigenvalue problem, are discussed. (C) 2000 Academic Press.
|
492. | Chan, TE, Sandberg, BY, and Vese, LA, "Active contours without edges for vector-valued images," JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, vol. 11, pp. 130-141, 2000.
Abstract:
In this paper, we propose an active contour algorithm for object
detection in vector-valued images (such as RGB or multispectral). The
model is an extension of the scalar Chan-Vese algorithm to the
vector-valued case [1]. The model minimizes a Mumford-Shah functional
over the length of the contour, plus the sum of the fitting error over
each component of the vector-valued image. Like the Chan-Vese model,
our vector-valued model can detect edges both with or without gradient.
We show examples where our model detects vector-valued objects which
are undetectable in any scalar representation. For instance, objects
with different missing parts in different channels are completely
detected (such as occlusion). Also, in color images, objects which are
invisible in each channel or in intensity can be detected by our
algorithm. Finally, the model is robust with respect to noise,
requiring no a priori denoising step. (C) 2000 Academic Press.
|
493. | Lepage, R, Rouhana, RG, St-Onge, B, Noumeir, R, and Desjardins, R, "Cellular neural network for automated detection of geological lineaments on radarsat images," IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 38, pp. 1224-1233, 2000.
Abstract:
The analysis of natural linear structures, termed "lineaments in
satellite images, provides important information to the geologist, In
the satellite imaging process, important features of the observed
tridimensional scene, including geological lineaments, are mapped into
the resulting 2-D image as sharp radiation variations or ed,ne elements
(edgels), Edgels are detected by a first-order differentiation operator
and are linked together with those in the vicinity on a basis of
orientation continuity.
Lineaments are mapped into remotely sensed satellite images as long and
continuous quasilinear features and can be described as a connected
sequence of edgels whose direction may change gradually along the
sequence. Parts of the same lineament can be occluded by
geomorphological features and must be linked together, a major drawback
with local and small neighborhood detectors.
We propose a cellular neural network (CNN) architecture to offer a
large directional neighborhood to the lineament detection algorithm.
The CNN uses a large circular neighborhood coupled with a
directional-induced gradient field to link together edgels with similar
and continuous orientation. Missing edgels are restored if a
surrounding lineament is detected.
|
494. | Oliver, N, Pentland, A, and Berard, F, "LAFTER: a real-time face and lips tracker with facial expression recognition," PATTERN RECOGNITION, vol. 33, pp. 1369-1382, 2000.
Abstract:
This paper describes an active-camera real-time system for tracking,
shape description, and classification of the human face and mouth
expressions using only a PC or equivalent computer. The system is based
on use of 2-D blob features, which are spatially compact clusters of
pixels that are similar in terms of low-level image properties.
Patterns of behavior (e.g., facial expressions and head movements) can
be classified in real-time using hidden Markov models (HMMs). The
system has been tested on hundreds of users and has demonstrated
extremely reliable and accurate performance. Typical facial expression
classification accuracies are near 100%. (C) 2000 Pattern Recognition
Society. Published by Elsevier Science Ltd. All rights reserved.
|
495. | Toklu, C, Tekalp, AM, and Erdem, AT, "Semi-automatic video object segmentation in the presence of occlusion," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol. 10, pp. 624-629, 2000.
Abstract:
We describe a semi-automatic approach for segmenting a video sequence
into spatio-temporal video objects in the presence of occlusion, Motion
and shape of each video object is represented by a 2-D mesh. Assuming
that the boundary of an object of interest is interactively marked on
some keyframes, the proposed method finds the boundary of the object in
all other frames automatically by tracking the 2-D mesh representation
of the object in both forward and backward directions. A key
contribution of the proposed method is automatic detection of covered
and uncovered regions at each frame, and assignment of pixels in the
uncovered regions to the object or background based on color and motion
similarity. Experimental results are presented on two MPEG-4 test
sequences and the resulting segmentations are evaluated both visually
and quantitatively.
|
496. | Sarti, A, Malladi, R, and Sethian, JA, "Subjective surfaces: A method for completing missing boundaries," PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, vol. 97, pp. 6258-6263, 2000.
Abstract:
We present a model and algorithm for segmentation of images with
missing boundaries. In many situations. the human visual system fills
in missing gaps in edges and boundaries, building and completing
information that is not present This presents a considerable challenge
in computer vision, since most algorithms attempt to exploit existing
data. Completion models, which postulate how to construct missing data,
are popular but are often trained and specific to particular images. In
this paper, we take the following perspective: We consider a reference
point within an image as given and then develop an algorithm that tries
to build missing information on the basis of the given point of view
and the available information as boundary data to the algorithm. We
test the algorithm on some standard images, including the classical
triangle of Kanizsa and low signal:noise ratio medical images.
|
497. | Imelinska, C, Downes, MS, and Yuan, W, "Semi-automated color segmentation of anatomical tissue," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 24, pp. 173-180, 2000.
Abstract:
We propose a semi-automated region-based color segmentation algorithm
to extract anatomical structures, including soft tissues, in the color
anatomy slices of the Visible Human data. Our approach is based on
repeatedly dividing an image into regions using Voronoi diagrams and
classifying the regions based on experimental classification
statistics. The user has the option of reclassifying regions in order
to improve the final boundary. Our results indicate that the algorithm
can find accurate outlines in a small number of iterations and that
manual interaction can markedly improve the outline. This approach can
be extended to 3D color segmentation. (C) 2000 Published by Elsevier
Science Ltd. All rights reserved.
|
498. | Kim, JS, Koh, KC, and Cho, HS, "An active contour model with shape regulation scheme," ADVANCED ROBOTICS, vol. 14, pp. 495-514, 2000.
Abstract:
This paper presents an active method for locating target objects in
images, which is aimed at improving the performance of detecting object
boundaries by enhancing the behavioral characteristics of an active
contour. The proposed active contour model simulates a mechanical
system consisting of two main parts: the first is a rigid fixture,
called the 'core' , specifying the expected shape of target boundaries,
while the second is an elastic rod attached to the rigid fixture. The
elastic rod deforms or moves relative to the rigid core according to
the classical laws of the mechanical system, When the initial contour
is applied to an image data, it is attracted near the dominant image
features, but tries to keep its home shape and simultaneously make the
deformation smooth if a deformation is more natural for force
equilibrium. This mechanism significantly improves the performance of
detecting object boundaries in the presence of some disturbing image
features. The active contour is scale invariant, thereby significantly
relieving the difficulty in selecting proper values for the model
parameters. The values for the model parameters can be selected to make
the contour have the desired behaviors around the equilibrium position
through the analysis of the vibration mode of the mechanical system.
The performance of the proposed method is validated through a series of
experiments, which include detection of heavily degraded objects,
tracking of objects under non-rigid motion and comparisons with the
original snake models.
|
499. | Egmont-Petersen, M, Schreiner, U, Tromp, SC, Lehmann, TM, Slaaf, DW, and Arts, T, "Detection of leukocytes in contact with the vessel wall from in vivo microscope recordings using a neural network," IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 47, pp. 941-951, 2000.
Abstract:
Leukocytes play an important role in the host defense as they may
travel from the blood stream into the tissue in reacting to
inflammatory stimuli. The leukocyte-vessel wall interactions are
studied in post capillary vessels by intraviral video microscopy during
in vivo animal experiments. Sequences of video images are obtained and
digitized with a frame grabber. A method for automatic detection and
characterization of leukocytes in the video images is developed.
Individual leukocytes are detected using a neural network that is
trained with synthetic leukocyte images generated using a novel
stochastic model. This model makes it feasible to generate images of
leukocytes with different shapes and sizes under various lighting
conditions. Experiments indicate that neural networks trained with the
synthetic leukocyte images perform better than networks trained with
images of manually detected leukocytes. The best performing neural
network trained with synthetic leukocyte images resulted in an 18%
larger area under the ROC curve than the best performing neural network
trained with manually detected leukocytes.
|
500. | Pardo, XM, and Cabello, D, "Biomedical active segmentation guided by edge saliency," PATTERN RECOGNITION LETTERS, vol. 21, pp. 559-572, 2000.
Abstract:
Deformable models are very popular approaches in biomedical image
segmentation. Classical snake models are edge-oriented and work well if
the target objects have distinct gradient values. This is not always
true in biomedical imagery, which makes the model very dependent on
initial conditions. In this work we propose an edge-based potential
aimed at the elimination of local minima due to undesired edges. The
new approach integrates knowledge about the features of the desired
boundaries apart from gradient strength and uses a new method to
eliminate local minima, which makes the segmentation less sensitive to
initial contours. (C) 2000 Elsevier Science B.V. All rights reserved.
|
501. | Chung, R, and Ho, CK, "3-D reconstruction from tomographic data using 2-D active contours," COMPUTERS AND BIOMEDICAL RESEARCH, vol. 33, pp. 186-210, 2000.
Abstract:
Reconstructing three-dimensional (3-D) shapes of structures like
internal organs from tomographic data is an important problem in
medical imaging. Various forms of the deformable surface model have
been proposed to tackle it, but they are either computationally
expensive or limited to tubular shapes. In this paper a 3-D
reconstruction mechanism that requires only 2-D deformations is
proposed. Advantages of the proposed model include that it is
conformable to any 3-D shape, efficient, and highly parallelizable.
Most importantly, it requires from the user an initial 2-D contour on
only one of the tomograph slices to start with. Experimental results
are shown to illustrate the performance of the model. (C) 2000 Academic
Press.
|
502. | Iannizzotto, G, and Vita, L, "Fast and accurate edge-based segmentation with no contour smoothing in 2-D real images," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 1232-1237, 2000.
Abstract:
In this paper we propose an edge-based segmentation algorithm built on
a new type of active contour which is fast, has a low computational
complexity and does not introduce unwanted smoothing on the retrieved
contours. The contours are always returned as closed chains of points,
resulting in a very useful base for subsequent shape representation
techniques.
|
503. | Wink, O, Niessen, WJ, and Viergever, MA, "Fast delineation and visualization of vessels in 3-D angiographic images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 337-346, 2000.
Abstract:
A method is presented which aids the clinician in obtaining
quantitative measures and a three-dimensional (3-D) representation of
vessels from 3-D angiographic data with a minimum of user interaction.
Based on two user defined starting points, an iterative procedure
tracks the central vessel axis. During the tracking process, the
minimum diameter and a surface rendering of the vessels are computed,
allowing for interactive inspection of the vasculature. Applications of
the method to CTA, contrast enhanced (CE)-MRA and phase contrast
(PC)-MRA images of the abdomen are shown, In all applications, a long
stretch of vessels with varying width is tracked, delineated, and
visualized, in less than 10 s on a standard clinical workstation.
|
504. | Chen, SJ, and Carroll, JD, "3-D reconstruction of coronary arterial tree to optimize angiographic visualization," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 318-336, 2000.
Abstract:
Due to vessel overlap and foreshortening, multiple projections are
necessary to adequately evaluate the coronary tree with arteriography,
Catheter-based interventions can only be optimally performed when these
visualization problems are successfully solved. The traditional method
provides multiple selected views in which overlap and foreshortening
are subjectively minimized based on two dimensional (2-D) projections.
A pair of images acquired from routine angiographic study at arbitrary
orientation using a single-plane imaging system were chosen far
three-dimensional (3-D) reconstruction. After the arterial segment of
interest (e.g., a single coronary stenosis or bifurcation lesion) was
selected, a set of gantry angulations minimizing segment foreshortening
was calculated. Multiple computer-generated projection images with
minimized segment foreshortening were then used to choose views with
minimal overlapped vessels relative to the segment of interest. The
optimized views could then be utilized to guide subsequent angiographic
acquisition and interpretation. Over 800 cases of coronary arterial
trees have been reconstructed, in which more than 40 cases were
performed in room during cardiac catheterization. The accuracy of 3-D
length measurement was confirmed to be within an average
root-mean-square (rms) 3.5% error using eight different pairs of
angiograms of an intracoronary guidewire of 105-mm length with eight
radiopaque markers of 15-mm interdistance. The accuracy of similarity
between the additional computer-generated projections versus the actual
acquired views was demonstrated with the average rms errors of 3.09 mm
and 3.13 mm in 20 LCA and 20 RCA cases, respectively. The projections
of the reconstructed patient-specific 3-D coronary tree model can be
utilized for planning optimal clinical views: minimal overlap and
foreshortening, The assessment of lesion length and diameter narrowing
can be optimized in both interventional cases and studies of disease
progression and regression.
|
505. | Suter, D, and Chen, F, "Left ventricular motion reconstruction based on elastic vector splines," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 295-305, 2000.
Abstract:
In medical imaging it is common to reconstruct dense motion estimates,
from sparse measurements of that motion, using some form of elastic
spline (thin-plate spline, snakes and other deformable models, etc.).
Usually the elastic spline uses only bending energy (second-order
smoothness constraint) or stretching energy (first-order smoothness
constraint), or a combination of the two. These elastic splines belong
to a family of elastic vector splines called the Laplacian splines.
This spline family is derived from an energy minimization functional,
which is composed of multiple-order smoothness constraints. These
splines can be explicitly tuned to vary the smoothness of the solution
according to the deformation in the modeled material/tissue.
In this context, it is natural to question which members of the family
will reconstruct the motion more accurately, We compare different
members of this spline family to assess how well these splines
reconstruct human cardiac motion. We find that the commonly used
splines (containing first-order and/or second-order smoothness terms
only) are not the most accurate for modeling human cardiac motion.
|
506. | Szekely, G, Brechbuhler, C, Dual, J, Enzler, R, Hug, J, Hutter, R, Ironmonger, N, Kauer, M, Meier, V, Niederer, P, Rhomberg, A, Schmid, P, Schweitzer, G, Thaler, M, Vuskovic, V, Troster, G, Haller, U, and Bajka, M, "Virtual reality-based simulation of endoscopic surgery," PRESENCE-TELEOPERATORS AND VIRTUAL ENVIRONMENTS, vol. 9, pp. 310-333, 2000.
Abstract:
Virtual reality (VR)-based surgical simulator systems offer a very
elegant approach to enriching and enhancing traditional training in
endoscopic surgery. However, while a number of VR simulator systems
have been proposed and realized in the past Few years, most of these
systems are far from being able to provide a reasonably realistic
surgical environment We explore the current limits for realism and the
approaches to reaching and surpassing those limits by describing and
analyzing the mast important components of VR-based endoscopic
simulators. The feasibility of the proposed techniques is demonstrated
on a modular prototype system that implements the basic algorithms for
VR training in gynaecologic laparoscopy.
|
507. | Tillett, R, McFarlane, N, and Lines, J, "Estimating dimensions of free-swimming fish using 3D point distribution models," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 79, pp. 123-141, 2000.
Abstract:
Monitoring the growth of farmed fish is an important task which is
currently difficult to carry out. An underwater stereo image analysis
technique offers the potential for estimating key dimensions of
free-swimming fish, from which the fish mass can be estimated. This
paper describes the development of a three-dimensional point
distribution model to capture the typical shape and variability of
salmon viewed from the side. The model was fitted to stereo images of
test fish by minimizing an energy function, which was based on
probability distributions. The minimization was an iterated two-step
method in which edges were selected for magnitude, direction, and
proximity to the model, and the model was then fitted to the edges. A
search strategy for locating the edges in 3D was devised. The model is
tested on two image sets. In the first set 19 of the 26 fish are
located in spite of their variable appearance and the presence of
neighboring fish. In the second set the measurements made on 11 images
of fish are compared with manual measurements of the fish dimensions
and show an average error in length estimation of 5%. (C) 2000 Academic
Press.
|
508. | Erlandsson, K, Visvikis, D, Waddington, WA, and Jarritt, P, "Truncation reduction in fan-beam transmission scanning using the radon transform consistency conditions," IEEE TRANSACTIONS ON NUCLEAR SCIENCE, vol. 47, pp. 989-993, 2000.
Abstract:
Transmission scanning is needed for accurate attenuation correction in
cardiac Single Photon Emission Tomography (SPET). Simultaneous emission
and transmission imaging can be done using a scintillation camera with
a fan-beam collimator and a line source at the focal point. The
transmission data will be truncated, however, which may lead to
inaccuracy in the reconstructed emission values. We have developed two
different methods for augmentation of truncated transmission data,
based on the Radon transform consistency conditions. Our results show
that the uniformity in the myocardium can be improved with these
methods, as compared to using the truncated data directly in the
reconstruction.
|
509. | Zhong, Y, Jain, AK, and Dubuisson-Jolly, MP, "Object tracking using deformable templates," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 544-549, 2000.
Abstract:
We propose a novel method for object tracking using prototype-based
deformable template models. To track an object in an image sequence, we
use a criterion which combines two terms: the frame-to-frame deviations
of the object shape and the fidelity of the modeled shape to the Input
image. The deformable template model utilizes the prior shape
information which is extracted from the previous frames along with a
systematic shape deformation scheme to model the object shape in a new
frame. The following image information Is used in the tracking process:
1) edge and gradient information: the object boundary consists of
pixels with large image gradient, 2) region consistency: the same
object region possesses consistent color and texture throughout the
sequence, and 3) interframe motion: the boundary of a moving object is
characterized by large interframe motion. The tracking proceeds by
optimizing an objective function which combines both the shape
deformation and the fidelity of the modeled shape to the current image
(in terms of gradient, texture, and interframe motion). The inherent
structure in the deformable template. together with region, motion, and
image gradient cues. makes the proposed algorithm relatively
insensitive to the adverse effects of weak image features and moderate
amounts of occlusion.
|
510. | Ma, WY, and Manjunath, BS, "EdgeFlow: A technique for boundary detection and image segmentation," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 1375-1388, 2000.
Abstract:
A novel boundary detection scheme based on "edge flow" is proposed in
this paper. This scheme utilizes a predictive coding model to identify
the direction of change in color and texture at each image location at
a given scale, and constructs an edge flow vector. By propagating the
edge flow vectors, the boundaries can be detected at image Locations
which encounter two opposite directions of flow in the stable state. A
user defined image scale is the only significant control parameter that
is needed by the algorithm. The scheme facilitates integration of color
and texture into a single framework for boundary detection.
Segmentation results on a large and diverse collections of natural
images are provided, demonstrating the usefulness of this method to
content based image retrieval.
|
511. | Haque, H, Hassanien, AE, and Nakajima, M, "Generation of missing medical slices using morphing technology," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E83D, pp. 1400-1407, 2000.
Abstract:
When the inter-slice resolution of tomographic image slices is large,
it is necessary to estimate the locations and intensities of pixels,
which would appear in the non-existed intermediate slices. This paper
presents a new method for generating the missing medical slices from
two given slices. It uses the contours of organs as the control
parameters to the intensity information in the physical gaps of
sequential medical slices. The Snake model is used for generating the
control points required for the elastic body spline (EBS) morphing
algorithm. Contour information derived from this segmentation
pre-process is then further processed and used as control parameters to
warp the corresponding regions in both input slices into compatible
shapes. In this way, the intensity information of the interpolated
intermediate slices can be derived more faithfully. In comparison with
the existing intensity interpolation methods, including linear
interpolation, which only considers corresponding points in a small
physical neighborhood, this method warps the data images into similar
shapes according to contour information to provide a more meaningful
correspondence relationship.
|
512. | Davison, NE, Eviatar, H, and Somarjai, RL, "Snakes simplified," PATTERN RECOGNITION, vol. 33, pp. 1651-1664, 2000.
Abstract:
The snake formulation of Eviatar and Somorjai has the advantages of
bring both conceptually simple and rapidly convergent. We extend this
formulation in two ways, by exploring additional energy terms whose
interpretation is transparent and by using a simple minimization
technique. The usefulness of the simplified model is illustrated using
artificial images as well as images obtained with MRI, optical
microscopy and ultrasound. (C) 2000 Published by Elsevier Science Ltd
on behalf of Pattern Recognition Society.
|
513. | Germond, L, Dojat, M, Taylor, C, and Garbay, C, "A cooperative framework for segmentation of MRI brain scans," ARTIFICIAL INTELLIGENCE IN MEDICINE, vol. 20, pp. 77-93, 2000.
Abstract:
Automatic segmentation of MRI brain scans is a complex task for two
main reasons: the large variability of the human brain anatomy, which
limits the use of general knowledge and, inherent to MRI acquisition,
the artifacts present in the images that are difficult to process. To
tackle these difficulties, we propose to mix, in a cooperative
framework, several types of information and knowledge provided and used
by complementary individual systems: presently, a multi-agent system, a
deformable model and an edge detector. The outcome is a cooperative
segmentation performed by a set of region and edge agents constrained
automatically and dynamically by both, the specific gray levels in the
considered image, statistical models of the brain structures and
general knowledge about MRI brain scans. Interactions between the
individual systems follow three modes of cooperation: integrative,
augmentative and confrontational cooperation, combined during the three
steps of the segmentation process namely, the specialization of the
seeded-region-growing agents, the fusion of heterogeneous information
and the retroaction over slices. The described cooperative framework
allows the dynamic adaptation of the segmentation process to the own
characteristics of each MRI brain scan. Its evaluation using realistic
brain phantoms is reported. (C) 2000 Elsevier Science B.V. All rights
reserved.
|
514. | Shelton, CR, "Morphable Surface Models," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 38, pp. 75-91, 2000.
Abstract:
We describe a novel automatic technique for finding a dense
correspondence between a pair of n-dimensional surfaces with arbitrary
topologies. This method employs a different formulation than previous
correspondence algorithms (such as optical flow) and includes images as
a special case. We use this correspondence algorithm to build Morphable
Surface Models (an extension of Morphable Models) from examples. We
present a method for matching the model to new surfaces and demonstrate
their use for analysis, synthesis, and clustering.
|
515. | Drummond, T, and Cipolla, R, "Application of Lie algebras to visual servoing," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 37, pp. 21-41, 2000.
Abstract:
A novel approach to visual servoing is presented, which takes advantage
of the structure of the Lie algebra of affine transformations. The aim
of this project is to use feedback from a visual sensor to guide a
robot arm to a target position. The target position is learned using
the principle of 'teaching by showing' in which the supervisor places
the robot in the correct target position and the system captures the
necessary information to be able to return to that position. The sensor
is placed in the end effector of the robot, the 'camera-in-hand'
approach, and thus provides direct feedback of the robot motion
relative to the target scene via observed transformations of the scene.
These scene transformations are obtained by measuring the affine
deformations of a target planar contour (under the weak perspective
assumption), captured by use of an active contour, or snake.
Deformations of the snake are constrained using the Lie groups of
affine and projective transformations. Properties of the Lie algebra of
affine transformations are exploited to provide a novel method for
integrating observed deformations of the target contour. These can be
compensated with appropriate robot motion using a non-linear control
structure. The local differential representation of contour
deformations is extended to allow accurate integration of an extended
series of small perturbations. This differs from existing approaches by
virtue of the properties of the Lie algebra representation which
implicitly embeds knowledge of the three-dimensional world within a
two-dimensional image-based system. These techniques have been
implemented using a video camera to control a 5 DoF robot arm.
Experiments with this implementation are presented, together with a
discussion of the results.
|
516. | Hobolth, A, and Jensen, EBV, "Modelling stochastic chances in curve shape, with an application to cancer diagnostics," ADVANCES IN APPLIED PROBABILITY, vol. 32, pp. 344-362, 2000.
Abstract:
Often, the statistical analysis of the shape of a random planar curve
is based on a model for a polygonal approximation to the curve. In the
present paper, we instead describe the curve as a continuous stochastic
deformation of a template curve. The advantage of this continuous
approach is that the parameters in the model do not relate to a
particular polygonal approximation. A somewhat similar approach has
been used by Kent et al. (1996), who describe the limiting behaviour of
a model with a first-order Markov property as the landmarks on the
curve become closely spaced; see also Grenander(1993). The model
studied in the present paper is an extension of this model. Our model
possesses a second-order Markov property. Its geometrical
characteristics are studied in some detail and an explicit expression
for the covariance function is derived. The model is applied to the
boundaries of profiles of cell nuclei from a benign tumour and a
malignant tumour. It turns out that the model with the second-order
Markov property is the most appropriate, and that it is indeed possible
to distinguish between the two samples.
|
517. | Tiddeman, B, Duffy, N, and Rabey, G, "Construction and visualisation of three-dimensional facial statistics," COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol. 63, pp. 9-20, 2000.
Abstract:
This paper presents a new method for the construction of
three-dimensional (3D) probabilistic Facial averages and demonstrates
the potential for applications in clinical craniofacial research and
patient assessment. Averages are constructed from a database of
registered laser-range scans and photographic images using feature
based image warping. Facial features are extracted using a template of
connected contours, adapted to each subject interactively using snakes.
Each subject's images are warped to the average template shape acid the
mean depth, colour and covariance matrix is found at each point.
Statistical comparison of individuals with an average or between two
averages is visualised by converting the probabilities to a coloured
texture map. (C) 2000 Elsevier Science Inland Ltd. All rights reserved.
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518. | Toklu, C, Erdem, AT, and Tekalp, AM, "Two-dimensional mesh-based mosaic representation for manipulation of video objects with occlusion," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 1617-1630, 2000.
Abstract:
We present a two-dimensional (2-D) mesh-based mosaic representation,
consisting of an object mesh and a mosaic mesh for each frame and a
final mosaic image, for video objects with mildly deformable motion in
the presence of self and/or object-to-object (external) occlusion,
Unlike classical mosaic representations where successive frames are
registered using global motion models, we map the uncovered regions in
the successive frames onto the mosaic reference frame using local
affine models, i.e., those of the neighboring mesh patches. The
proposed method to compute this mosaic representation is tightly
coupled with an occlusion adaptive 2-D mesh tracking procedure, which
consist of propagating the object mesh frame to frame, and updating of
both object and mosaic meshes to optimize texture mapping from the
mosaic to each instance of the object. The proposed representation has
been applied to video object rendering and editing, including self
transfiguration, synthetic transfiguration, and 2-D augmented reality
in the presence of self and/or external occlusion, We also provide an
algorithm to determine the minimum number of still views needed to
reconstruct a replacement mosaic which is needed for synthetic
transfiguration. Experimental results are provided to demonstrate both
the 2-D mesh-based mosaic synthesis and two different video object
editing applications on real video sequences.
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519. | Brigger, P, Hoeg, J, and Unser, M, "B-Spline snakes: A flexible tool for parametric contour detection," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 1484-1496, 2000.
Abstract:
We present a novel formulation for B-spline snakes that can be used as
a tool for fast and intuitive contour outlining. We start with a
theoretical argument in favor of splines in the traditional formulation
by showing that the optimal, curvature-constrained snake is a cubic
spline, irrespective of the form of the external energy held,
Unfortunately, such regularized snakes suffer from slow convergence
speed because of a large number of control points, as well as from
difficulties in determining the weight factors associated to the
internal energies of the curve. We therefore propose an alternative
formulation in which the intrinsic scale of the spline model is
adjusted a priori; this Leads to a reduction of the number of
parameters to be optimized and eliminates the need for internal
energies (i.e., the regularization term), In other words, we are now
controlling the elasticity of the spline implicitly and rather
intuitively by varying the spacing between the spline knots. The theory
is embedded into a multiresolution formulation demonstrating improved
stability in noisy image environments. Validation results are
presented, comparing the traditional snake using internal energies and
the proposed approach without internal energies, showing the similar
performance of the latter, Several biomedical examples of applications
are included to illustrate the versatility of the method.
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520. | Bertalmio, M, Sapiro, G, and Randall, G, "Morphing active contours," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 733-737, 2000.
Abstract:
A method for deforming curves in a given image to a desired position in
the second image is introduced in this paper. The algorithm is based on
deforming the first image toward the second one via a Partial
Differential Equation (PDE), while tracking the deformation of the
curves of interest in the first image with an additional, coupled, PDE.
The tracking is performed by projecting the velocities of the first
equation into the second one. In contrast with previous PDE-based
approaches, both the images and the curves on the frames/slices of
interest are used for tracking. The technique can be applied to object
tracking and sequential segmentation. The topology of the deforming
curve can change without any special topology handling procedures added
to the scheme. This permits, for example, the automatic tracking of
scenes where, due to occlusions, the topology of the objects of
interest changes from frame to frame. In addition, this work introduces
the concept of projecting velocities to obtain systems of coupled PDEs
for image analysis applications We show examples for object tracking
and segmentation of electronic microscopy.
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521. | Nikolaidis, A, and Pitas, I, "Facial feature extraction and pose determination," PATTERN RECOGNITION, vol. 33, pp. 1783-1791, 2000.
Abstract:
A combined approach for facial feature extraction and determination of
gaze direction is proposed that employs some improved variations of the
adaptive Hough transform for curve detection, minima analysis of
feature candidates, template matching for inner facial feature
localization, active contour models for inner face contour detection
and projective geometry properties for accurate pose determination. The
aim is to provide a sufficient set of features for further use in a
face recognition or face tracking system. (C) 2000 Pattern Recognition
Society. Published by Elsevier Science Ltd. All rights reserved.
|
522. | Chen, CM, Lu, HHS, and Lin, YC, "An early vision-based snake model for ultrasound image segmentation," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 26, pp. 273-285, 2000.
Abstract:
Due to the speckles and the ill-defined edges of the object of
interest, the classic image-segmentation techniques are usually
ineffective in segmenting ultrasound (US) images. In this paper, we
present a new algorithm for segmenting general US images that is
composed of two major techniques; namely, the early-vision model and
the discrete-snake model, By simulating human early vision, the
early-vision model can capture both grey-scale and textural edges while
the speckle noise is suppressed. By performing deformation only on the
peaks of the distance map, the discrete-snake model promises better
noise immunity and more accurate convergence. Moreover, the constraint
for most conventional snake models that the initial contour needs to be
located very close to the actual boundary has been relaxed
substantially. The performance of the proposed snake model has been
shown to be comparable to manual delineation and superior to that of
the gradient vector flow (GVF) snake model. (C) 2000 World Federation
for Ultrasound in Medicine & Biology.
|
523. | Garrido, A, and de la Blanca, NP, "Applying deformable templates for cell image segmentation," PATTERN RECOGNITION, vol. 33, pp. 821-832, 2000.
Abstract:
This paper presents an automatic method. based on the deformable
template approach, for cell image segmentation under severe noise
conditions. We define a new methodology, dividing the process into
three parts: (1) obtain evidence from the image about the location of
the cells, (2) use this evidence to calculate an elliptical
approximation of these locations; (3) refine cell boundaries using
locally deforming models. We have designed a new algorithm to locate
cells and propose an energy function to be used together with 3
stochastic deformable template model. Experimental results show that
this approach for segmenting cell images is both Fast and robust, and
that this methodology may be used for automatic classification as part
of a computer-aided medical decision making technique. (C) 2000 Pattern
Recognition Society. Published by Elsevier Science Ltd, All rights
reserved.
|
524. | Falcao, AX, Udupa, JK, and Miyazawa, FK, "An ultra-fast user-steered image segmentation paradigm: Live wire on the fly," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 55-62, 2000.
Abstract:
We have been developing general user steered image segmentation
strategies for routine use in applications involving a large number of
data sets. In the past, we have presented three segmentation paradigms:
live wire, live lane, and a three-dimensional (3-D) extension of the
live-wire method. In this paper, we introduce an ultra-fast live-wire
method, referred to as live wire on the fly, for further reducing
user's time compared to the basic live-wire method. In live wire,
3-D/four-dimensional (4-D) object boundaries are segmented in a
slice-by-slice fashion. To segment a two-dimensional (2-D) boundary,
the user initially picks a point on the boundary and all possible
minimum-cost paths from this point to all other points in the image are
computed via Dijkstra's algorithm. Subsequently a live wire is
displayed in real time From the initial point to any subsequent
position taken by the cursor. If the cursor is close to the desired
boundary, the live wire snaps on to the boundary. The cursor is then
deposited and a new live-wire segment is Found next, The entire 2-D
boundary is specified via a set of live-wire segments in this fashion.
A drawback of this method is that the speed of optimal path computation
depends on image size. On modestly powered computers, for images of
even modest size, some sluggishness appears in user interaction, which
reduces the overall segmentation efficiency. In this work, we solve
this problem by exploiting some known properties of graphs to avoid
unnecessary minimum-cost path computation during segmentation. In live
wire on the fly, when the user selects a point on the boundary the
live-wire segment is computed and displayed in real time from the
selected point to any subsequent position of the cursor in the image,
even for large images and even on low-powered computers. Based on 492
tracing experiments from an actual medical application, we demonstrate
that live wire on the fly is 1.3-31 times faster than live wire for
actual segmentation for varying image sizes, although the pure
computational part alone is found to be about 120 times faster.
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525. | Chen, YM, Vemuri, BC, and Wang, L, "Image denoising and segmentation via nonlinear diffusion," COMPUTERS & MATHEMATICS WITH APPLICATIONS, vol. 39, pp. 131-149, 2000.
Abstract:
Image denoising and segmentation are fundamental problems in the field
of image processing and computer vision with numerous applications. In
this paper, we present a nonlinear PDE-based model for image denoising
and segmentation which unifies the popular model of Alvarez, Lions and
Morel (ALM) for image denoising and the Caselles, Kimmel and Sapiro
model of geodesic "snakes". Our model includes nonlinear diffusive as
well as reactive terms and leads to quality denoising and segmentation
results as depicted in the experiments presented here. We present a
proof for the existence, uniqueness, and stability of the viscosity
solution of this PDE-based model. The proof is in spirit similar to the
proof of the ALM model; how ever, there are several differences which
arise due to the presence of the reactive terms that require careful
treatment/consideration. A fast implementation of our model is realized
by embedding the model in a scale space and then achieving the solution
via a dynamic system governed by a coupled system of first-order
differential equations. The dynamic system finds the solution at a
coarse scale and tracks it continuously to a desired fine scale. We
demonstrate the smoothing and segmentation results on several real
images. (C) 2000 Elsevier Science Ltd. All rights reserved.
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526. | Pollak, I, Willsky, AS, and Krim, H, "Image segmentation and edge enhancement with stabilized inverse diffusion equations," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 256-266, 2000.
Abstract:
We introduce a family of first-order multidimensional ordinary
differential equations (ODE's) with discontinuous right-hand sides and
demonstrate their applicability in image processing. An equation
belonging to this family is an inverse diffusion everywhere except at
local extrema, where some stabilization is introduced. For this reason,
we call these equations "stabilized inverse diffusion equations"
(SIDE's), Existence and uniqueness of solutions, as well as stability,
are proven for SIDE's, A SIDE in one spatial dimension may be
interpreted as a limiting case of a semi-discretized Perona-Malik
equation [14], [15], In an experimental section, SIDE's are shown to
suppress noise while sharpening edges present in the input signal,
Their application to image segmentation is also demonstrated.
|
527. | Lee, WS, and Magnenat-Thalmann, N, "Fast head modeling for animation," IMAGE AND VISION COMPUTING, vol. 18, pp. 355-364, 2000.
Abstract:
This paper describes an efficient method to make individual faces for
animation from several possible inputs. We present a method to
reconstruct a three-dimensional (3D) facial model for animation from
two orthogonal pictures taken from front and side views, or from range
data obtained from any available resources. It is based on extracting
features on a face in a semiautomatic way and modifying a generic model
with detected feature points. Then fine modifications follow if range
data is available. Automatic texture mapping is employed using an image
composed from the two images. The reconstructed 3D-face can be animated
immediately with given expression parameters. Several faces by obtained
one methodology applied to different input data to get a final
animatable face are illustrated. (C) 2000 Elsevier Science B.V. All
rights reserved.
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528. | Lengagne, R, Fua, P, and Monga, O, "3D stereo reconstruction of human faces driven by differential constraints," IMAGE AND VISION COMPUTING, vol. 18, pp. 337-343, 2000.
Abstract:
Conventional stereo algorithms often fail in accurately reconstructing
a 3D object because the image data do not provide enough information
about the geometry of the object. We propose a way to incorporate a
priori information in a reconstruction process from a sequence of
calibrated face images. A 3D mesh modeling the face is iteratively
deformed in order to minimize an energy function. Differential
information extracted from the object shape is used to generate an
adaptive mesh. We also propose to explicitly incorporate a priori
constraints related to the differential properties of the surface where
the image information cannot yield an accurate shape recovery. (C) 2000
Elsevier Science B.V. All rights reserved.
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529. | Blank, M, and Kalender, WA, "Medical volume exploration: gaining insights virtually," EUROPEAN JOURNAL OF RADIOLOGY, vol. 33, pp. 161-169, 2000.
Abstract:
Since modern imaging modalities deliver huge amounts of data, which
cannot be assessed easily, the visualization techniques are utilized to
emphasize the structures of interest. To compare them, the different
visualization techniques (maximum intensity projection, multiplanar
reformations, shaded surface display and volume rendering) are
regressed to a common ground whereby their strengths and weaknesses can
be revealed. Additionally, medical image analysis can detect anatomical
objects in volumetric data sets and provides their descriptions for
further use. Usually, segmentation plays a crucial roll in that
process. There are many segmentation methods which can be categorized
in boundary-based and content-based ones. The extraction of anatomical
objects also allows their quantification. Image analysis and
visualization do not squeeze more information out of a data volume, but
they provide different ways to look at it. As in real life, this alone
may enlarge the insight. (C) 2000 Elsevier Science Ireland Ltd. All
rights reserved.
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530. | Lei, ZB, and Lin, YT, "3D shape inferencing and modeling for video retrieval," JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, vol. 11, pp. 41-57, 2000.
Abstract:
We present a geometry-based indexing approach for the retrieval of
video databases. It consists of two modules: 3D object shape
inferencing from video data and geometric modeling from the
reconstructed shape structure. A motion-based segmentation algorithm
employing feature block tracking and principal component split is used
for multi-moving-object motion classification and segmentation. After
segmentation, feature blocks from each individual object are used to
reconstruct its motion and structure through a factorization method.
The estimated shape structure and motion parameters are used to
generate the implicit polynomial model for the object. The video data
is retrieved using the geometric structure of objects and their spatial
relationship. We generalize the 2D string to 3D to compactly encode the
spatial relationship of objects. (C) 2000 Academic Press.
|
531. | Shishido, O, Yoshida, N, and Umino, O, "Image processing experiments for computer-based three-dimensional reconstruction of neurones from electron micrographs from serial ultrathin sections," JOURNAL OF MICROSCOPY-OXFORD, vol. 197, pp. 224-238, 2000.
Abstract:
This study examined an image processing technique that uses a computer
to reconstruct a three-dimensional image of neurones from electron
micrographs of serial ultrathin sections. The major problems involved
were: (a) a distortion of features in electron micrographs; (b) a
significant change of cross-section features of neurones in electron
micrographs of neighbouring sections; and (c) disagreement between the
electron microscopic section face and the coordinate plane desired for
the reconstruction. Electron micrographs of a retinal bipolar cell
stained with a biotinylated tracer were used. We corrected the
distortion of features by means of a warp, a widely used algorithm in
morphing image processing. The change of features between neighbouring
electron micrographs was minimized by filling the gaps with an
interpolated image produced by a dissolve, another algorithm in
morphing, as well as the warp. The distortion of the three-dimensional
reconstructed image made by piling up features was corrected by making
the image with a wire frame model. Furthermore, in order to estimate a
closed contour of features, an active contour model, Snakes, was
applied to the electron microscope features. Snakes successfully
detected the contour of the target feature, but in some electron
microscope images broke into the target feature.
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532. | Rabben, SI, Torp, AH, Stoylen, A, Slordahl, S, Bjornstad, K, Haugen, BO, and Angelsen, B, "Semiautomatic contour detection in ultrasound M-mode images," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 26, pp. 287-296, 2000.
Abstract:
We have developed a method for semiautomatic contour detection in
M-mode images. The method combines tissue Doppler and grey-scale data,
It was used to detect: 1. the left endocardium of the septum, the
endocardium and epicardium of the posterior wall in 16 left ventricular
short-axis M-modes, and 2. the mitral ring in 38 anatomical M-modes
extracted pair-wise in 19 apical four-chamber cine-loops (healthy
subjects). We validated the results by comparing the computer-generated
contours with contours manually outlined by four echocardiographers.
For all boundaries, the average distance between the computer-generated
contours and the manual outlines was smaller than the average distance
between the manual outlines. We also calculated left ventricular wall
thickness and diameter at end-diastole and end-systole and lateral and
septal mitral ring excursions, and found, on average, clinically
negligible differences between the computer-generated indices and the
same indices based on manual outlines (0.8-1.8 mm), The results were
also within published normal values. In conclusion, this initial study
showed that it was feasible in a robust and efficient manner to detect
continuous wall boundaries in M-mode images so that tracings of left
ventricular wall thickness, diameter and long axis could be derived.
(C) 2000 World Federation for Ultrasound in Medicine & Biology.
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533. | MacDonald, D, Kabani, N, Avis, D, and Evans, AC, "Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI," NEUROIMAGE, vol. 12, pp. 340-356, 2000.
Abstract:
Automatic computer processing of large multidimensional images such as
those produced by magnetic resonance imaging (MRI) is greatly aided by
deformable models, which are used to extract, identify, and quantify
specific neuroanatomic structures. A general method of deforming
polyhedra is presented here, with two novel features, First, explicit
prevention of self-intersecting surface geometries is provided, unlike
conventional deformable models, which use regularization constraints to
discourage but not necessarily prevent such behavior. Second,
deformation of multiple surfaces with intersurface proximity
constraints allows each surface to help guide other surfaces into place
using model-based constraints such as expected thickness of an anatomic
surface. These two features are used advantageously to identify
automatically the total surface of the outer and inner boundaries of
cerebral cortical gray matter from normal human MR images, accurately
locating the depths of the sulci, even where noise and partial volume
artifacts in the image obscure the visibility of sulci. The extracted
surfaces are enforced to be simple two-dimensional manifolds (having
the topology of a sphere), even though the data may have topological
holes, This automatic 3-D cortex segmentation technique has been
applied to 150 normal subjects, simultaneously extracting both the
gray/white and gray/cerebrospinal fluid interface from each individual.
The collection of surfaces has been used to create a spatial map of the
mean and standard deviation for the location and the thickness of
cortical gray matter. Three alternative criteria for defining cortical
thickness at each cortical location were developed and compared. These
results are shown to corroborate published postmortem and in vivo
measurements of cortical thickness. (C) 2000 Academic Press.
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534. | Zhong, Y, and Jain, AK, "Object localization using color, texture and shape," PATTERN RECOGNITION, vol. 33, pp. 671-684, 2000.
Abstract:
We address the problem of localizing objects using color, texture and
shape. Given a handrawn sketch for querying an object shape. and its
color and texture, the proposed algorithm automatically searches the
image database for objects which meet the query attributes. The
database images do not need to be presegmented or annotated. The
proposed algorithm operates in two stages. In the first stage, we use
local texture and color features to find a small number of candidate
images in the database, and identify regions in the candidate images
which share similar texture and color as the query. To speed up the
processing, the texture and color features are directly extracted from
the Discrete Cosine Transform (DCT) compressed domain. In the second
stage. we use a deformable template matching method to match the query
shape to the image edges at the locations which possess the desired
texture and color attributes. This algorithm is different from other
content-based image retrieval algorithms in that: (i) no
presegmentation of the database images is needed, and (ii) the color
and texture features are directly extracted from the compressed images.
Experimental results demonstrate performance of the algorithm and show
that substantial computational savings can be achieved by utilizing
multiple image cues. (C) 2000 Pattern Recognition Society. Published by
Elsevier Science Ltd. All rights reserved.
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535. | Suri, JS, Haralick, RM, and Sheehan, FH, "Greedy algorithm for error correction in automatically produced boundaries from low contrast ventriculograms," PATTERN ANALYSIS AND APPLICATIONS, vol. 3, pp. 39-60, 2000.
Abstract:
Non-homogeneous mixing of the dye with the blood in the left ventricle
chamber of the heart causes poor contrast in the ventriculograms. The
pixel-based classifiers [1] operating on these ventriculograms yield
boundaries which are not close to ground truth boundaries as delineated
by the cardiologist. They have a mean boundary error of 6.4 mm and an
error of 12.5 mm in the apex zone. These errors have a systematic
positional and orientational bias, the boundary being under-estimated
in the apex zone. This paper discusses two calibration methods: the
identical coefficient and the independent coefficient to remove these
systematic biases. From these methods, we constitute a fused algorithm
which reduces the boundary error compared to either of the calibration
methods. The algorithm, in a greedy way, computes which and how many
vertices of the left ventricle boundary can be taken from the computed
boundary of each method in order to best improve the performance. The
corrected boundaries have a mean error of less than 3.5 mm with a
standard deviation of 3.4 mm over the approximately 6 x 10(4) vertices
in the data set of 291 studies. Our method reduces the mean boundary
error by 2.9 mm over the boundary produced by the classifier. We also
show that the calibration algorithm performs better in the apex zone
where the dye is unable to propagate. For end diastole, the: algorithm
reduces the error in the apex zone by 8.5 mm over the pixel-based
classifier boundaries.
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536. | Blom, AS, Pilla, JJ, Pusca, SV, Patel, HJ, Dougherty, L, Yuan, Q, Ferrari, VA, Axel, L, and Acker, MA, "Dynamic cardiomyoplasty decreases myocardial workload as assessed by tissue tagged MRI," ASAIO JOURNAL, vol. 46, pp. 556-562, 2000.
Abstract:
The effects of dynamic cardiomyoplasty (CMP) on global and regional
left ventricular (LV) function in end-stage heart failure still remain
unclear. MRI with tissue-tagging is a novel tool for studying
intramyocardial motion and mechanics. To date, no studies have
attempted to use MRI to simultaneously study global and regional
cardiac function in a model of CMP. In this study, we used MRI with
tissue-tagging and a custom designed MR compatible muscle
stimulating/pressure monitoring system to assess long axis regional
strain and displacement variations, as well as changes in global LV
function in a model of dynamic cardiomyoplasty. Three dogs underwent
rapid ventricular pacing (RVP; 215 BPM) For 10 weeks; after 4 weeks of
RVP, a left posterior CMP was performed. After 1 year of dynamic muscle
stimulation, the dogs were imaged in a 1.5 T clinical MR scanner.
Unstimulated and muscle stimulated tagged long axis images were
acquired. Quantitative 2-D regional image analysis was performed by
dividing the hearts into three regions: apical, septal, and lateral.
Maximum and minimum principal strains (lambda(1) and lambda(2)) and
displacement (D) were determined and pooled for each region. MR LV
pressure-volume (PV) loops were also generated. Muscle stimulation
produced a leftward shift of the PV loops in two of the three dogs, and
an increase in the peak LV pressure, while stroke volume remained
unchanged. With stimulation, lambda(1) decreased significantly (p <
0.05) in the lateral region, whereas lambda(2) increased significantly
(p < 0.05) in both the lateral and apical regions, indicating a
decrease in strain resulting from stimulation. D only increased
significantly (p < 0.05) in the apical region. The decrease in strain
between unassisted and assisted states indicates the heart is
performing less work, while maintaining stroke volume and increasing
peak LV pressure. These findings demonstrate that the muscle wrap
functions as an active assist, decreasing the workload of the heart,
while preserving total pump performance.
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537. | Shen, DG, and Davatzikos, C, "An adaptive-focus deformable model using statistical and geometric information," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 906-913, 2000.
Abstract:
An active contour (snake) model is presented, with emphasis on medical
imaging applications. There are three main novelties in the proposed
model. First. an attribute vector is used to characterize the geometric
structure around each point of the snake model: the deformable model
then deforms in a way that seeks regions with similar attribute
vectors. This is in contrast to most deformable models, which deform to
nearby edges without considering geometric structure. and it was
motivated by the need to establish point-correspondences that have
anatomical meaning. Second, an adaptive-focus statistical model has
been suggested which allows the deformation of the active contour in
each stage to be influenced primarily by the most reliable matches.
Third, a deformation mechanism that is robust to local minima is
proposed by evaluating the snake energy function on segments of the
snake at a time, instead of individual points. Various experimental
results show the effectiveness of the proposed model.
|
538. | Jeon, BK, Jang, JH, and Hong, KS, "Map-based road detection in spaceborne synthetic aperture radar images based on curvilinear structure extraction," OPTICAL ENGINEERING, vol. 39, pp. 2413-2421, 2000.
Abstract:
This paper presents an automatic map-based road detection algorithm for
spaceborne synthetic aperture radar (SAR) images. Our goal is to find
roads in a SAR image with subpixel accuracy with the help of a digital
map. There are location errors between the digital map and the geocoded
SAR image, which are about 20 to 30 pixels, and we adopt a
coarse-to-fine strategy to reduce it. In the coarse matching step, we
roughly find the locations of roads by a simple search using water
areas or a generalized Hough transform based on digital map
information. The fine matching step detects roads accurately by using
the active contour model (snake). The input of the snake operation is
the potential field constructed from the extracted ridges or ravines of
curvilinear structures in the SAR image. Experimental results show that
our algorithm detects roads with average error of less than one pixel,
(C) 2000 Society of Photo-Optical Instrumentation Engineers.
[S0091-3286(00)01309-X].
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539. | Haacke, EM, and Liang, ZP, "Challenges of imaging structure and function with MRI," IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, vol. 19, pp. 55-62, 2000.
Abstract:
A semi-automatic system for determining volumes of interest (VOI) from
positron emission tomography (PET) scans of brain is described. The
VOIs surface extraction is based on user selectable threshold and
three-dimensional target flood-fill. Contrast to anatomical volume
detection approaches, Volumes are determined from functional PET images
and the obtained objects are checked against anatomical images. The
developed VOI program was evaluated with brain FDOPA-PET studies where
the striatum was the object. The results were comparable to entirely
manual method and the target extraction time is reduced to about one
third of manual method. (C) 2000 Elsevier Science Ireland Ltd. All
rights reserved.
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540. | Mykkanen, JM, Juhola, M, and Ruotsalainen, U, "Extracting VOIs from brain PET images," INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, vol. 58, pp. 51-57, 2000.
Abstract:
A semi-automatic system for determining volumes of interest (VOI) from
positron emission tomography (PET) scans of brain is described. The
VOIs surface extraction is based on user selectable threshold and
three-dimensional target flood-fill. Contrast to anatomical volume
detection approaches, Volumes are determined from functional PET images
and the obtained objects are checked against anatomical images. The
developed VOI program was evaluated with brain FDOPA-PET studies where
the striatum was the object. The results were comparable to entirely
manual method and the target extraction time is reduced to about one
third of manual method. (C) 2000 Elsevier Science Ireland Ltd. All
rights reserved.
|
541. | Maksimovic, R, Stankovic, S, and Milovanovic, D, "Computed tomography image analyzer: 3D reconstruction and segmentation applying active contour models - 'snakes'," INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, vol. 58, pp. 29-37, 2000.
Abstract:
Many diagnostic and therapeutic procedures depend on medical images. In
order to overcome imperfections of the obtained images, which are due
to the acquisition process, and to extract new information from the
available images, many techniques have been developed. In this study, a
new method of image segmentation and 3D reconstruction based on active
contour models ('snakes') was applied in analyzing computed tomography
(CT) images in patients with acute head trauma. Using this method,
lesion to brain (LBR) and ventricle to brain ratio (VBR) parameters, as
well as 3D reconstruction of traumatic lesion, was obtained accurately.
In our study group, 215 patients (mean age 42.4 +/- 23.5 years, 138/215
(64.2%) males) were included. Among them, 72 (33.5%) did not survive
during hospitalisation in the Emergency Department. LBR correlated with
the Glasgow Coma Score and the intrahospital outcome (r = -0.457 and r
= 0.515, respectively). Besides, non-survivors had greater LTB values
(0.042 +/- 0.034) than survivors (0.005 +/- 0.011). However, VER did
not correlate with these clinical parameters. In addition, LBR was
significantly higher in the patients with other pathologic CT findings.
The proposed methodology, based on extracting maximum information from
available CT scans, could be a basis for further medical decision
making in patients with acute head trauma. (C) 2000 Elsevier Science
Ireland Ltd. All rights reserved.
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542. | Rodriguez-Sanchez, R, Garcia, JA, Fdez-Valdivia, J, and Fdez-Vidal, XR, "Origins of illusory percepts in digital images," PATTERN RECOGNITION, vol. 33, pp. 2007-2017, 2000.
Abstract:
Here we show the relation between illusory percepts and statistical
regularities across scales and orientations. To this aim, the
performance of a computational model for the partitioning of
statistical regularities is analyzed on several tasks such as
long-range boundary completion, phase-induced contour detection, as
well as shape and size illusions. The system for the automatically
learned partitioning of statistical regularities in 2D images, is based
on a sophisticated, band-pass, filtering operation, with fixed scale
and orientation sensitivity. Experimental results are provided to
illustrate this analysis on several examples: (i) Kanizsa-type
subjective figures; (ii) phase-induced subjective contours; (iii) the
Zollner illusion; and (iv) the Muller-Lyer illusion. (C) 2000 Pattern
Recognition Society. Published by Elsevier Science Ltd. All rights
reserved.
|
543. | Yang, WF, and Smith, MR, "Using an MRI distortion transfer function to characterize the ghosts in motion-corrupted images," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 577-584, 2000.
Abstract:
Motion artefact suppression remains an active topic in MRI. In this
paper, we suggest that certain nonrigid, or spatially variant,
characteristics of motion of an object can be represented by extending
the work of Mitsa et al, This empirical extension uses a ghost
distortion transfer function (GTDF) applied to the k-space (frequency
domain) data. We demonstrate the variety of ghost characteristics that
can be generated from various two-dimensional (2-D) GTDF's, The
distortion transfer function for periodic motion along the Z-axis can
be determined from the nonoverlapped portions of the ghost and central
image, It required a GDTF with the shape of a belt bandpass filter to
produce an image corresponding to the ghosts of a volunteer's abdomen
image corrupted by unknown respiratory motion artefacts, The
preliminary results of a composite method of motion artefact
suppression are presented. The artefact suppression was successful for
ghost images described by a GDTF have a low-pass nature, but less
successful with ghosts have a GDTF of a bandpass nature.
|
544. | Yoshida, H, and Keserci, B, "Bayesian wavelet snake for computer-aided diagnosis of lung nodules," INTEGRATED COMPUTER-AIDED ENGINEERING, vol. 7, pp. 253-269, 2000.
Abstract:
An edge-guided active contour based on the wavelet transform called the
Bayesian wavelet snake has been developed for identifying a
closed-contour object with a fuzzy and low-contrast boundary. The
wavelet snake is designed to deform its shape based on a maximum a
posteriori estimate calculated by the fast wavelet transform. Our new
method was applied to a computer-aided diagnosis scheme for detection
of pulmonary nodules in digital chest radiographs. In this scheme, a
filter based on the edge gradient was employed for enhancement of
nodules, followed by creation of multiscale edges by spline wavelets
for extraction of portions of the boundary of a candidate nodule. These
multiscale edges are then used to "guide" the wavelet snake for
estimation of the boundary of the nodule. The degree of overlap between
the resulting snake and the multiscale edges was used as a feature for
distinguishing nodules from false-positive detections that consist of
only normal anatomic structures. The wavelet snake was combined with
morphological features by means of an artificial neural network for
further reduction of false detections. The performance of our scheme
was evaluated by receiver operating characteristic analysis based on a
publicly available database of chest radiographs.
|
545. | Senasli, M, Garnero, L, Herment, A, and Mousseaux, E, "3D reconstruction of vessel lumen from very few angiograms by dynamic contours using a stochastic approach," GRAPHICAL MODELS, vol. 62, pp. 105-127, 2000.
Abstract:
3D luminal vessel geometry description and visualization are important
for the diagnosis and the prognosis of heart attack and stroke. A
general mathematical framework is proposed for 3D reconstruction of
vessel sections from a few angiograms, Regularization is introduced by
modeling the vessel boundary slices by smooth contours to get the
reconstruction problem well posed. A dynamic contour approach is
applied to optimize the shape of the contour according to the recorded
angiograms and the internal smoothness constraints. The solution is
achieved following the minimization of a nonconvex energy function
assigned to the contour with a simulated annealing algorithm.
Preliminary testing on noisy and truncated synthetic images produces
promising results, Evaluation and validation of the method on hardware
phantoms are also presented. (C) 2000 Academic Press.
|
546. | Lurig, C, Kobbelt, L, and Ertl, T, "Hierarchical solutions for the deformable surface problem in visualization," GRAPHICAL MODELS, vol. 62, pp. 2-18, 2000.
Abstract:
In this paper we present a hierarchical approach for the deformable
surface technique. This technique is a three dimensional extension of
the snake segmentation method. We use it in the context of visualizing
three dimensional scalar data sets. In contrast to classical indirect
volume visualization methods, this reconstruction is not based on
iso-values but on boundary information derived from discontinuities in
the data. We propose a multilevel adaptive finite difference solver,
which generates a target surface minimizing an energy functional based
on an internal energy of the surface and an outer energy induced by the
gradient of the volume. The method is attractive for preprocessing in
numerical simulation or texture mapping. Red-green triangulation allows
adaptive refinement of the mesh. Special considerations help to prevent
self interpenetration of the surfaces. We will also show some
techniques that introduce the hierarchical aspect into the
inhomogeneity of the partial differential equation. The approach proves
to be appropriate for data sets that contain a collection of objects
separated by distinct boundaries. These kind of data sets often occur
in medical and technical tomography, as we will demonstrate in a few
examples. (C) 2000 Academic Press.
|
547. | Paragios, N, and Deriche, R, "Geodesic active contours and level sets for the detection and tracking of moving objects," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 266-280, 2000.
Abstract:
This paper presents a new variational framework for detecting and
tracking multiple moving objects in image sequences. Motion detection
is performed using a statistical framework for which the observed
interframe difference density function is approximated using a mixture
model. This model is composed of two components, namely, the static
(background) and the mobile (moving objects) one. Both components are
zero-mean and obey Laplacian or Gaussian law. This statistical
framework is used to provide the motion detection boundaries.
Additionally, the original frame is used to provide the moving object
boundaries. Then, the detection and the tracking problem are addressed
in a common framework that employs a geodesic active contour objective
function. This function is minimized using a gradient descent method,
where a flow deforms the initial curve towards the minimum of the
objective function, under the influence of internal and external image
dependent forces. Using the level set formulation scheme, complex
curves can be detected and tracked white topological changes for the
evolving curves are naturally managed. To reduce the computational cost
required by a direct implementation of the level set formulation
scheme, a new approach named Hermes is proposed. Hermes exploits
aspects from the well-known front propagation algorithms (Narrow Band.
Fast Marching) and compares favorably to them. Very promising
experimental results are provided using real video sequences.
|
548. | Cremers, D, Schnorr, C, Weickert, J, and Schellewald, C, "Diffusion-snakes using statistical shape knowledge," ALGEBRAIC FRAMES FOR THE PERCEPTION-ACTION CYCLE, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1888, pp. 164-174, 2000.
Abstract:
We present a novel extension of the Mumford-Shah functional that allows
to incorporate statistical shape knowledge at the computational level
of image segmentation. Our approach exhibits various favorable
properties: non-local convergence, robustness against noise, and the
ability to take into consideration both shape evidence in given image
data and knowledge about learned shapes. In particular, the latter
property distinguishes our approach from previous work on
contour-evolution based image segmentation. Experimental results
confirm these properties.
|
549. | Ravi, D, "A new active contour model for shape extraction," MATHEMATICAL METHODS IN THE APPLIED SCIENCES, vol. 23, pp. 709-722, 2000.
Abstract:
We propose a new active contour model for shape extraction of objects
in grey-valued two-dimensional images based on an energy-minimization
formulation. The energy functional that we consider takes into account
the two requirements of object isolation and smoothness of the contour.
After deriving the Euler-Lagrange equations corresponding to the energy
functional, we bring out some important geometric properties of a
solution to these equations. The discussion on our solution method-with
the help of which we try to minimize the energy functional by evolving
an initial curve-also focuses on how to prescribe the initial curve
fully automatically. The effectiveness of our algorithms is
demonstrated with the help of experimental results. Copyright (C) 2000
John Wiley & Sons, Ltd.
|
550. | Chung, DH, and Sapiro, G, "Segmenting skin lesions with partial-differential-equations-based image processing algorithms," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 763-767, 2000.
Abstract:
In this paper, a partial-differential equations (PDE)-based system for
detecting the boundary of skin lesions in digital clinical skin images
is presented. The image is first preprocessed via contrast-enhancement
and anisotropic diffusion. If the lesion is covered by hairs, a
PDE-based continuous morphological filter that removes them is used as
an additional preprocessing step. Following these steps, the skin
lesion is segmented either by the geodesic active contours model or the
geodesic edge tracing approach. These techniques are based on
computing, again via PDEs, a geodesic curve in a space defined by the
image content. Examples showing the performance of the algorithm are
given.
|
551. | Xuan, JH, Adali, T, Wang, Y, and Siegel, E, "Automatic detection of foreign objects in computed radiography," JOURNAL OF BIOMEDICAL OPTICS, vol. 5, pp. 425-431, 2000.
Abstract:
This paper presents an effective two-step scheme for automatic object
detection in computed radiography (CR) images. First, various structure
elements of the morphological filters, designed by incorporating
available morphological features of the objects of interest including
their sizes and rough shape descriptions, are used to effectively
distinguish the foreign object candidates from the complex background
structures. Second, since the boundaries of the objects are the key
features in reflecting object characteristics, active contour models
are employed to accurately outline the morphological shapes of the
suspicious foreign objects to further reduce the rate of false alarms.
The actual detection scheme is accomplished by jointly using these two
steps. The proposed methods are tested with a database of 50 hand-wrist
computed radiographic images containing various types of foreign
objects. Our experimental results demonstrate that the combined use of
morphological filters and active contour models can provide an
effective automatic detection of foreign objects in CR images achieving
good sensitivity and specificity, and the accurate descriptions of the
object morphological characteristics. (C) 2000 Society of Photo-Optical
Instrumentation Engineers. [S1083-3668(00)00704-8].
|
552. | Ida, T, and Sambonsugi, Y, "Self-affine mapping system and its application to object contour extraction," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 1926-1936, 2000.
Abstract:
A self-affine mapping system which has conventionally been used to
produce fractal images is used to fit rough lines to contours. The
self-affine map's parameters are detected by analyzing the blockwise
self-similarity of a grayscale image using a simplified algorithm in
fractal encoding. The phenomenon that edges attract mapping points in
self-affine mapping is utilized in the proposed method. The boundary of
the foreground region of an alpha mask is fitted by mapping iterations
of the region. It is shown that the proposed method accurately produces
not only smooth curves but also sharp corners, and has the ability to
extract both distinct edges and blurred edges using the same parameter.
It is also shown that even large gaps between the hand-drawn line and
the contour can be fitted well by the recursive procedure of the
proposed algorithm, in which the block size is progressively decreased.
These features reduce the time required for drawing contours by hand.
|
553. | Suri, JS, "Computer vision, pattern recognition and image processing in left ventricle segmentation: The last 50 years," PATTERN ANALYSIS AND APPLICATIONS, vol. 3, pp. 209-242, 2000.
Abstract:
In the last decade, computer vision, pattern recognition, image
processing and cardiac researchers have given immense attention to
cardiac image analysis and modelling. This paper surveys
state-of-the-are computer vision and pattern recognition techniques for
Left Ventricle (LV) segmentation and modelling juring the second half
of the twentieth century The paper presents the key characteristics of
successful model-based segmentation techniques for LV modelling. This
sun ey paper concludes the following: (1) any one pattern recognition
or computer vision technique is nut sufficient for accurate 2D, 3D or
4D modelling of LV; (2) fitting mathematical models for LV modelling
have dominated in the last 15 years; (3) knowledge extracted from the
ground truth has lead to very successful attempts at LV modelling; (4)
spatial and temporal behaviour of LV through different imaging
modalities has yielded information which has led to accurate LV
modelling; and (5) not much attention has bern paid to LV modelling
validation.
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554. | Wang, HY, and Ghosh, B, "Geometric active deformable models in shape modeling," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 9, pp. 302-308, 2000.
Abstract:
This paper analyzes the problem of shape modeling using the principle
of active geometric deformable models. While the basic modeling
technique already exists in the literature, we highlight many of its
drawbacks and discuss their source and steps to overcome them. We
propose a new stopping criterion to address the stopping problem. We
also propose to apply level set algorithm to implement the active
geometric deformable models, thereby handling topology changes
automatically. To alleviate the numerical problems associated with the
implementation of the level set algorithm, we propose a new adaptive
multigrid narrow band algorithm. All the proposed new changes have been
illustrated with experiments with synthetic images and medical images.
|
555. | Park, J, and Park, SI, "Strain analysis and visualization: left ventricle of a heart," COMPUTERS & GRAPHICS-UK, vol. 24, pp. 701-714, 2000.
Abstract:
Clinical utility of computational models is crucial in the applications
of medical data visualization. Previously we have developed a new class
of volumetric models whose parameters are functions in conjunction with
physically based deformable modeling framework, and have applied the
technique to estimate the left ventricular (LV) wall motion. We have
successfully showed that the model parameter functions characterize the
LV motion of normal and abnormal stares and that no further non-trivial
post-processing is required for anatomically meaningful interpretation.
In an effort to evaluate the LV model, this paper presents a method and
results from a strain analysis based on the nodal displacements of the
deformable LV model. Furthermore, in order to visualize the local
quantities on the volumetric model for an effective analysis, we also
developed a methodology to assist in assessing the cardiac function
utilizing principal strains, Von-Mises' yield criteria, and a smoothing
filter. Each strain tensor component,vas in the range of values
observed in other reported studies. The application of a smoothing
filter on the model improved in visualizing the overall trend of each
strain variation. With our platform for a comprehensive strain
analysis, we have augmented a clinical utility to the deformable models
with parameter functions, (C) 2000 Elsevier Science Ltd. All rights
reserved.
|
556. | Shin, H, Stamm, G, Hogemann, D, and Galanski, M, "Basic principles of data acquisition and data processing in the construction of high-quality virtual models," RADIOLOGE, vol. 40, pp. 304-312, 2000.
Abstract:
Creating models for virtual reality subdivides into several steps. The
aim of the data acquisition is the extraction of nearly isotropic (same
solution in all three axes) data sets with low noise content. An
approximate isotropy can be achieved by suitable choice of scan
parameters. For raw data reconstruction, the application of
high-resolution reconstruction algorithms is prohibited due to
increased noise. A missing isotropy can computationally be approximated
by interpolation. Further noise suppression is achieved by applying
filters. Additionally, the contrast of the object for segmentation can
be increased by image processing operators. The correct choice of the
segmentation method and the editing tools is essential for a precise
segmentation with minimal user interaction. Prior to
visualization,smoothing the shape of the segmented model (shape-based
or morphological interpolation, polygon reduction of wire frame model)
further improves the visual appearance of the 3D model.
|
557. | Loreti, P, and March, R, "Propagation of fronts in a nonlinear fourth order equation," EUROPEAN JOURNAL OF APPLIED MATHEMATICS, vol. 11, pp. 203-213, 2000.
Abstract:
We consider a geometric motion associated with the minimization of a
curvature dependent functional. which is related to the Willmore
functional. Such a functional arises in connection with the image
segmentation problem in computer vision theory. We show by using formal
asymptotics that the geometric motion can be approximated by the
evolution of the zero level set of the solution of a nonlinear
fourth-order equation related to the Cahn-Hilliard and Allen-Cahn
equations.
|
558. | Kovalski, G, Beyar, R, Shofti, R, and Azhari, H, "Three-dimensional automatic quantitative analysis of intravascular ultrasound images," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 26, pp. 527-537, 2000.
Abstract:
Intravascular ultrasound (IVUS) has established itself as a useful tool
for coronary assessment, The vast amount of data obtained by a single
IVUS study renders manual analysis impractical for clinical use, A
computerized method is needed to accelerate the process and eliminate
user-dependency. In this study, a new algorithm is used to identify the
lumen border and the media-adventitia border (the external elastic
membrane). Setting an initial surface on the IVUS catheter perimeter
and using active contour principles, the surface inflates until virtual
force equilibrium defined by the surface geometry and image features is
reached, The method extracts these features in three dimensions (3-D),
Eight IVUS procedures were performed using an automatic pullback
device. Using the ECG signal for synchronization, sets of images
covering the entire studied region and corresponding to the same
cardiac phase were sampled. Lumen and media-adventitia border contours
were traced manually and compared to the automatic results obtained by
the suggested method. Linear regression results for vessel area
enclosed by the lumen and media-adventitia border indicate high
correlation between manual vs, automatic tracings (y = 1.07 x -0.38; r
= 0.98; SD = 0.112 mm(2); n = 88), These results indicate that the
suggested algorithm may potentially provide a clinical tool for
accurate lumen and plaque assessment. (C) 2000 World Federation for
Ultrasound in Medicine & Biology.
|
559. | Magnenat-Thalmann, N, and Cordier, F, "Construction of a human topological model from medical data," IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, vol. 4, pp. 137-143, 2000.
Abstract:
Medical imaging can provide data for useful views of the interior
details of human anatomy. In addition to visualization, which in
general has been the primary reason for obtaining these data, many
other uses are possible, These include modeling of different elements
and their inter-relationships-topological modeling, simulation of
physical processes, analysis of movements, and validation of models,
Here, we describe some of the modeling issues from medical imaging. The
issues are particularly related to topological modeling of different
anatomical elements: bones, muscles, articulations, etc. A
three-dimensional topological modeler is presented with which
anatomists and other users can build a topological database containing
structural, topological, and mechanical information of anatomical
elements.
|
560. | Viblis, MK, and Kyriakopoulos, KJ, "Gesture recognition: The gesture segmentation problem," JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, vol. 28, pp. 151-158, 2000.
Abstract:
The gesture segmentation problem is introduced as the first step
towards visual gesture recognition i.e. with the detection, analysis
and recognition of gestures from sequences of real images. Our gesture
segmentation scheme is composed of two steps: accurate gesture contour
tracking in space domain, and continuous tracking in time domain.
Experimental results and implementations issues are presented.
|
561. | Urayama, S, Matsuda, T, Sugimoto, N, Mizuta, S, Yamada, N, and Uyama, C, "Detailed motion analysis of the left ventricular myocardium using an MR tagging method with a dense grid," MAGNETIC RESONANCE IN MEDICINE, vol. 44, pp. 73-82, 2000.
Abstract:
Detailed analysis of myocardial deformation through a whole cardiac
cycle was accomplished using a tagging method with a high-density grid.
Four sets of tagged images with a 4-mm-spacing grid were measured by
generating four tagging pulses arranged at regular intervals in the
cardiac cycle. Through each set of images, tag intersections were
tracked semi-automatically. The estimated motions of tag intersections
were concatenated so that sequential positions of myocardium were
connected through a whole cardiac cycle. In vitro evaluation of the
precision of this technique showed that the mean error of tracked 4-mm
tag intersections was less than 0.47 +/- 0.17 mm, even on the quite
low-contrast images, and the concatenation error caused by double
concatenation was comparable to the interpolation error in the
subendocardial area obtained with 8-mm tag intersection motion. The
small difference between the two mean distance curves of the in vivo
evaluation indicated that the method is useful for analyzing heart wall
abnormalities. (C) 2000 Wiley-Liss, Inc.
|
562. | Samson, C, Blanc-Feraud, L, Aubert, G, and Zerubia, J, "A variational model for image classification and restoration," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 460-472, 2000.
Abstract:
Herein, we present a variational model devoted to image classification
coupled with an edge-preserving regularization process. The discrete
nature of classification (i.e., to attribute a label to each pixel) has
led to the development of many probabilistic image classification
models, but rarely to variational ones. In the last decade, the
variational approach has proven its efficiency in the field of
edge-preserving restoration. In this paper, we add a classification
capability which contributes to provide images composed of homogeneous
regions with regularized boundaries, a region being defined as a set of
pixels belonging to the same class. The soundness of our model is based
on the works developed on the phase transition theory in mechanics. The
proposed algorithm is fast, easy to implement, and efficient. We
compare our results on both synthetic and satellite images with the
ones obtained by a stochastic model using a Potts regularization.
|
563. | Vemuri, BC, and Guo, YL, "Snake pedals: Compact and versatile geometric models with physics-based control," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 22, pp. 445-459, 2000.
Abstract:
In this paper, we introduce a novel geometric shape modeling scheme
which allows for representation of global and local shape
characteristics of an object. Geometric models are traditionally
well-suited for representing global shapes without local detail.
However, we propose a powerful geometric shape modeling scheme which
allows for the representation of global shapes with local detail and
permits model shaping as well as topological changes via physics-based
control. The proposed modeling scheme consists of representing shapes
by pedal curves and surfaces-pedal curves/surfaces are the loci of the
foot of perpendiculars to the tangents of a fixed curve/surface from a
fixed point called the pedal point. By varying the location of the
pedal point, one can synthesize a large class of shapes which exhibit
both local and global deformations. We introduce physics-based control
for shaping these geometric models by letting the pedal point vary and
use a snake to represent the position of this varying pedal point. The
model dubbed as a "snake pedal" allows for interactive manipulation via
forces applied to the snake. We develop a fast numerical iterative
algorithm for shape recovery from image data using this geometric shape
modeling scheme. The algorithm involves the Levenberg-Marquardt (LM)
method in the outer loop for solving the global parameters and the
Alternating Direction Implicit (ADI) method in the inner loop for
solving the local parameters of the model. The combination of the
global and local scheme leads to an efficient numerical solution to the
model fitting problem. We demonstrate the applicability of this
modeling scheme via examples of shape synthesis and shape estimation
from real image data.
|
564. | Shih, WSV, Lin, WC, and Chen, CT, "Volumetric morphologic deformation method for intersubject image registration," INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, vol. 11, pp. 117-124, 2000.
Abstract:
An automated image processing method is proposed for anatomic
standardization that can elastically map one subject's magnetic
resonance image (MRI) to a standard reference MRI to enable
intersubject and cross-group studies. In this method, linear
transformations based on bicommissural stereotaxy are first applied to
grossly align the input image to the reference image. Then. the
candidate corresponding regions in the input image are identified based
on the contour information from the presegmented reference image. Next,
an active contour model is employed to refine the contour description
of the input image. Based on the contour correspondence established in
these previous steps, a nonlinear transformation is determined using
the proposed weighted local reference coordinate systems to warp the
input Image. In this method, geometric correspondence established based
on contour matching is used to control the warping and the actual image
values corresponding to registered coordinates need not be similar. We
tested this algorithm on various synthetic and real images for
intersubject registration of MRIs. (C) 2000 John Wiley & Sons, Inc.
|
565. | Laptev, I, Mayer, H, Lindeberg, T, Eckstein, W, Steger, C, and Baumgartner, A, "Automatic extraction of roads from aerial images based on scale space and snakes," MACHINE VISION AND APPLICATIONS, vol. 12, pp. 23-31, 2000.
Abstract:
We propose a new approach for automatic road extraction from aerial
imagery with a model and a strategy mainly based on the multi-scale
detection of roads in combination with geometry-constrained edge
extraction using snakes. A main advantage of our approach is, that it
allows for the first time a bridging of shadows and partially occluded
areas using the heavily disturbed evidence in the image. Additionally,
it has only few parameters to be adjusted. The road network is
constructed after extracting crossings with varying shape and topology.
We show the feasibility of the approach not only by presenting
reasonable results but also by evaluating them quantitatively based on
ground truth.
|
566. | Grace, AE, Pycock, D, Tillotson, HT, and Snaith, MS, "Active shape from stereo for highway inspection," MACHINE VISION AND APPLICATIONS, vol. 12, pp. 7-15, 2000.
Abstract:
This paper describes an unsupervised algorithm for estimating the 3D
profile of potholes in the highway surface, using structured
illumination. Structured light is used to accelerate computation and to
simplify the estimation of range. A low-resolution edge map is
generated so that further processing may be focused on relevant regions
of interest. Edge points in each region of interest are used to
initialise open, active contour models, which are propagated and
refined, via a pyramid, to a higher resolution. At each resolution,
internal and external constraints are applied to a snake; the internal
constraint is a smoothness function and the external one is a
maximum-likelihood estimate of the grey-level response at the edge of
each light stripe. Results of a provisional evaluation study indicate
that this automated procedure provides estimates of pothole dimension
suitable for use in a first, screening, assessment of highway condition.
|
567. | Frost, AR, Tillett, RD, and Welch, SK, "The development and evaluation of image analysis procedures for guiding a livestock monitoring sensor placement robot," COMPUTERS AND ELECTRONICS IN AGRICULTURE, vol. 28, pp. 229-242, 2000.
Abstract:
The over all objective of the work described here is to develop a
robotic system capable of holding a sensor in contact with any one of a
set of pre-determined positions on the body of a loosely constrained
live animal. This paper is concerned with generating sets of
coordinates corresponding to the target points on the animal's body.
The problem was approached using image analysis. Models were
established to predict the positions of arbitrary points on the body of
a pig from the positions of features in the image of the periphery of
the pig, which could be measured automatically. From measurements of
the movements of pigs in a feeding stall it was shown that the
resultant error in the predicted position of an arbitrary point on the
pig's body was comparable to that which could be expected from a human
operator. The approach of using image analysis to guide a livestock
monitoring sensor placement robot shows considerable Promise. and is
worthy of further investigation. Future work should concentrate on
establishing the generality of target point prediction models. (C) 2000
Elsevier Science B.V. All rights reserved.
|
568. | Haber, I, Metaxas, DN, and Axel, L, "Using tagged MRI to reconstruct a 3D heartbeat," COMPUTING IN SCIENCE & ENGINEERING, vol. 2, pp. 18-30, 2000.
Abstract:
Magnetic resonance imaging tissue tagging is a decade-old method that
lets scientists follow the motion of a beating heart. The method
described here reconstructs 3D motion from multiple 2D MRI images to
find new information about the right ventricle.
|
569. | Tannenbaum, A, "On the eye tracking problem: a challenge for robust control," INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, vol. 10, pp. 875-888, 2000.
Abstract:
Eye tracking is one of the key problems in controlled active vision.
Because of modelling uncertainty and noise in the signals, it becomes a
challenging problem for robust control. In this paper, we outline some
of the key issues involved as well as some possible solutions. We will
need to make contact with techniques from machine vision and
multi-scale image processing in carrying out this task. In particular,
we will sketch some of the necessary methods from computer vision and
image processing including optical flow, active contours ('snakes'),
and geometric driven flows. The paper will thus have a tutorial flavor
as well. Copyright (C) 2000 John Wiley & Sons, Ltd.
|
570. | Fan, LX, Santago, P, Jiang, H, and Herrington, DM, "Ultrasound measurement of brachial flow-mediated vasodilator response," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 621-631, 2000.
Abstract:
Brachial artery flow-mediated vasodilation is increasingly used as a
measure of endothelial function. High resolution ultrasound provides a
noninvasive method to observe this flow-mediated vasodilation by
monitoring the diameter of the artery over time following a transient
flow stimulus. Since hundreds of ultrasound images are required to
continuously monitor brachial diameter for the 2-3 min during which the
vasodilator response occurs, an automated diameter estimation is
desirable. However, vascular ultrasound images suffer from structural
noise caused by the constructive and destructive interference of the
backscattered signals, and the true boundaries of interest that define
the diameter are frequently obscured by the multiple-layer structure of
the vessel wall, These problems make automated diameter estimation
strategies based on the detection of the vessel wall boundary
difficult. We obtain a robust automated measurement of the vasodilator
response by automatically locating the artery using a variable window
method, which gives both the lumen center and width. The vessel wall
boundary is detected by a global constraint deformable model, which is
insensitive to the structural noise in the boundary area, The ambiguity
between the desired boundary and other undesired boundaries is resolved
by a spatiotemporal strategy. Our method provides excellent
reproducibility both for interreader and intrareader analyzes of
percent change in diameter, and has been successfully used in analyzing
over 4000 brachial flow-mediated vasodilation scans from several
medical centers in the United States.
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571. | Chiueh, TC, Mitra, T, Neogi, A, and Yang, CK, "Zodiac: A history-based interactive video authoring system," MULTIMEDIA SYSTEMS, vol. 8, pp. 201-211, 2000.
Abstract:
Easy-to-use audio/video authoring tools play a crucial role in moving
multimedia software from research curiosity to mainstream applications.
However, research in multimedia authoring systems has rarely been
documented in the literature. This paper describes the design and
implementation of an interactive video authoring system called Zodiac,
which employs an innovative edit history abstraction to support several
unique editing features not found in existing commercial and research
video editing systems. Zodiac provides users a conceptually clean and
semantically powerful branching history model of edit operations to
organize the authoring process, and to navigate among versions of
authored documents. In addition, by analyzing the edit history, Zodiac
is able to reliably detect a composed video stream's shot and scene
boundaries, which facilitates interactive video browsing. Zodiac also
features a video object annotation capability that allows users to
associate annotations to moving objects in a video sequence. The
annotations themselves could be text, image, audio, or video. Zodiac is
built on top of MMFS, a file system specifically designed for
interactive multimedia development environments, and implements an
internal buffer manages that supports transparent lossless
compression/decompression. Shot/scene detection, video object
annotation, and buffer management all exploit the edit history
information for performance optimization.
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572. | Brejl, M, and Sonka, M, "Object localization and border detection criteria design in edge-based image segmentation: Automated learning from examples," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 973-985, 2000.
Abstract:
This paper provides methodology for fully automated model-based image
segmentation. All information necessary to perform image segmentation
is automatically derived from a training set that is presented in a
form of segmentation examples, The training set is used to construct
two models representing the objects-shape model and border appearance
model.
A two-step approach to image segmentation is reported. In the first
step, an approximate location of the object of interest is determined.
In the second step, accurate border segmentation is performed. The
shape-variant Hough transform method was developed that provides robust
object localization automatically. It finds objects of arbitrary shape,
rotation, or scaling and can handle object variability, The border
appearance model was developed to automatically design cost functions
that can be used in the segmentation criteria of edge based
segmentation methods.
Our method was tested in five different segmentation tasks that
included 489 objects to be segmented. The final segmentation was
compared to manually defined borders with good results [rms errors in
pixels: 1.2 (cerebellum), 1.1 (corpus callosum), 1.5 (vertebrae), 1.4
(epicardial), and 1.6 (endocardial) borders],
Two major problems of the state-of-the-art edge based image
segmentation algorithms were addressed: strong dependency on a
close-to-target initialization, and necessity for manual redesign of
segmentation criteria whenever new segmentation problem is encountered.
|
573. | Davies, ER, "Low-level vision requirements," ELECTRONICS & COMMUNICATION ENGINEERING JOURNAL, vol. 12, pp. 197-210, 2000.
Abstract:
This paper aims to help those with some experience of vision to obtain
a more in-depth understanding of the problems of low-level vision. As
it is not possible to cover everything in a paper of this length, a
carefully chosen series of cases and case studies is presented.
Relevant principles are brought out and a set of important ground rules
is presented by way of summary.
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574. | Treece, GM, Prager, RW, Gee, AH, and Berman, L, "Surface interpolation from sparse cross sections using region correspondence," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 1106-1114, 2000.
Abstract:
The ability to estimate a surface from a set of cross sections allows
calculation of the enclosed volume and the display of the surface in
three-dimensions. This process has increasingly been used to derive
useful information from medical data. However, extracting the cross
sections (segmenting) can be very difficult, and automatic segmentation
methods are not sufficiently robust to handle all situations. Hence, it
is an advantage if the surface reconstruction algorithm can work
effectively on a small number of cross sections. In addition, cross
sections of medical data are often quite complex. Shape-based
interpolation is a simple and elegant solution to this problem,
although it has known Limitations when handling complex shapes. In this
paper, the shape-based interpolation paradigm is extended to
interpolate a surface through sparse, complex cross sections, providing
a significant improvement over our previously published maximal
disc-guided interpolation, The performance of this algorithm is
demonstrated on various types of medical data (X-ray computed
tomography, magnetic resonance imaging and three-dimensional
ultrasound). Although the correspondence problem in general remains
unsolved, it is demonstrated that correct surfaces can be estimated
from a limited amount of real data, through the use of region rather
than object correspondence.
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575. | Shiffman, S, Rubin, GD, and Napel, S, "Medical image segmentation using analysis of isolable-contour maps," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 19, pp. 1064-1074, 2000.
Abstract:
A common challenge for automated segmentation techniques is
differentiation between images of close objects that have similar
intensities, whose boundaries are often blurred due to partial-volume
effects. We propose a novel approach to segmentation of two-dimensional
images, which addresses this challenge. Our method, which we call
intrinsic shape for segmentation (ISeg), analyzes isolabel-contour maps
to identify coherent regions that correspond to major objects. ISeg
generates an isolabel-contour map for an image by multilevel
thresholding with a fine partition of the intensity range, ISeg detects
object boundaries by comparing the shape of neighboring isolabel
contours from the map. ISeg requires only little effort from users; it
does not require construction of shape models of target objects. In a
formal validation with computed-tomography angiography data, we showed
that ISeg was more robust than conventional thresholding, and that
ISeg's results were comparable to results of manual tracing.
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576. | Sanchez, PJ, Zapata, J, and Ruiz, R, "An active contour model algorithm for tracking endocardiac boundaries in echocardiographic sequences," CRITICAL REVIEWS IN BIOMEDICAL ENGINEERING, vol. 28, pp. 487-492, 2000.
Abstract:
The use of active contour models to track the boundaries of anatomic
structures in medical images is a technique that has attracted a great
number of efforts during the last decade. Segmentation techniques based
in deformable active contours were proposed first by Kass et al.(1)
Because of the problems appearing using these models, some solutions
have been introduced, such as balloon force(2) or Gradient Vector Flow
force (GVF), derived from the Gradient Vector Flow vectorial field.(3)
Results obtained with these forces in the tracking endocardiac task in
echocardiographic sequences were not adequate. We have designed a new
external force called hybrid force, which, by combining both forces,
joins the main features of each one.
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577. | Positano, V, Mammoliti, R, Santarelli, MF, Landini, L, and Benassi, A, "Nonlinear analysis of carotid artery echographic images," IEE PROCEEDINGS-SCIENCE MEASUREMENT AND TECHNOLOGY, vol. 147, pp. 327-332, 2000.
Abstract:
Nonlinear analysis is applied to identifying complex spatial patterns
in echographic images of normal and pathologic carotid arteries.
Complexity and entropy measures of normal and atherosclerotic plaques
are evaluated to characterise the space-temporal evolution of
biological patterns. They are: correlation dimension, Lyapunov exponent
and Kolmogorov entropy. The application of principal component analysis
to such measures clusters data according to different atherosclerosis
severity degrees, which are confirmed by histologic analysis.
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578. | Samson, C, Blanc-Feraud, L, Aubert, G, and Zerubia, J, "A level set model for image classification," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 40, pp. 187-197, 2000.
Abstract:
We present a supervised classification model based on a variational
approach. This model is devoted to find an optimal partition composed
of homogeneous classes with regular interfaces. The originality of the
proposed approach concerns the definition of a partition by the use of
level sets. Each set of regions and boundaries associated to a class is
defined by a unique level set function. We use as many level sets as
different classes and all these level sets are moving together thanks
to forces which interact in order to get an optimal partition. We show
how these forces can be defined through the minimization of a unique
fonctional. The coupled Partial Differential Equations (PDE) related to
the minimization of the functional are considered through a dynamical
scheme. Given an initial interface set (zero level set), the different
terms of the PDE's are governing the motion of interfaces such that, at
convergence, we get an optimal partition as defined above. Each
interface is guided by internal forces (regularity of the interface),
and external ones (data term, no vacuum, no regions overlapping).
Several experiments were conducted on both synthetic and real images.
|
579. | Krucker, JF, Meyer, CR, LeCarpentier, GL, Fowlkes, JB, and Carson, PL, "3D spatial compounding of ultrasound images using image-based nonrigid registration," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 26, pp. 1475-1488, 2000.
Abstract:
Medical ultrasound images are often distorted enough to significantly
limit resolution during compounding (i.e., summation of images from
multiple views). A new, volumetric image registration technique has
been used successfully to enable high spatial resolution in
three-dimensional (3D) spatial compounding of ultrasound images.
Volumetric ultrasound data were acquired by scanning a linear matrix
array probe in the elevational direction in a focal lesion phantom and
in a breast in vitro. To obtain partly uncorrelated views, the volume
of interest was scanned at five different transducer tilt angles
separated by 4 degrees to 6 degrees. Pairs of separate views were
registered by an automatic procedure based on a mutual information
metric, using global full affine and thin-plate spline warping
transformations. Registration accuracy was analyzed automatically in
the phantom data, and manually in vivo, yielding average registration
errors of 0.31 mm and 0.65 mm, respectively. In the vicinity of the
warping control points, registrations obtained with warping
transformations were significantly more accurate than full affine
registrations. Compounded images displayed the expected reduction in
speckle noise and increase in contrast-to-noise ratio (CNR), as well as
better delineation of connective tissues and reduced shadowing.
Compounding also revealed some apparent low contrast lobulations that
were not visible in the single-sweep images. Given expected algorithmic
and hardware enhancements, nonrigid, image-based registration shows
great promise for reducing tissue motion and refraction artifacts in 3D
spatial compounding. (C) 2001 World Federation for Ultrasound in
Medicine & Biology.
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580. | Lo Presti, L, D'Amato, G, and Sambuelli, L, "Two-dimensional random adaptive sampling for image scanning," IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, vol. 38, pp. 2608-2616, 2000.
Abstract:
In this paper, an efficient sampling algorithm for image scanning is
proposed, suitable to represent "interesting" objects, defined as a set
of spatially close measured values that springs out from a background
noise (as in applied geophysics in the process of anomaly detection).
This method generates a map of pixels randomly distributed in the plane
and able to cover all the image with a reduced number of points with
respect to a regular scanning, Simulation results show that a saving
factor of about 50% is obtained without information loss, This result
can be proved also by using a simplified model of the sampling
mechanism. The algorithm is able to detect the presence of an object
emerging from a low energy background and to adapt the sampling
interval to the shape of the detected object. In this way, all of the
interesting objects are well represented and can be adequately
reconstructed, while the roughly sampling in the background produces an
imperfect reconstruction.
Simulation results show that the method is feasible with good
performances and moderate complexity.
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581. | Falcao, AX, and Udupa, JK, "A 3D generalization of user-steered live-wire segmentation," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 389-402, 2000.
Abstract:
We have been developing user-steered image segmentation methods for
situations which require considerable human assistance in object
definition. In the past, we have presented two paradigms, referred to
as live-wire and live-lane, for segmenting 2D/3D/4D object boundaries
in a slice-by-slice fashion, and demonstrated that live-wire and
live-lane are more repeatable, with a statistical significance level of
P < 0.03, and are 1.5-2.5 times faster, with a statistical significance
level of P < 0.02, than manual tracing. In this paper, we introduce a
3D generalization of the live-wire approach for segmenting 3D/4D object
boundaries which further reduces the time spent by the user in
segmentation. In a 2D live-wire, given a slice, for two specified
points (pixel vertices) on the boundary of the object, the best
boundary segment is the minimum-cost path between the two points,
described as a set of oriented pixel edges. This segment is found via
Dijkstra's algorithm as the user anchors the first point and moves the
cursor to indicate the second point. A complete 2D boundary is
identified as a set of consecutive boundary segments forming a
"closed", "connected", "oriented" contour. The strategy of the 3D
extension is that, first, users specify contours via live-wiring on a
few slices that are orthogonal to the natural slices of the original
scene. If these slices are selected strategically, then we have a
sufficient number of points on the 3D boundary of the object to
subsequently trace optimum boundary segments automatically in all
natural slices of the 3D scene. A 3D object boundary may define
multiple 2D boundaries per slice. The points on each 2D boundary form
an ordered set such that when the best boundary segment is computed
between each pair of consecutive points, a closed, connected, oriented
boundary results. The ordered set of points on each 2D boundary is
found from the way the users select the orthogonal slices. Based on
several validation studies involving segmentation of the bones of the
foot in MR images, we found that the 3D extension of live-wire is more
repeatable, with a statistical significance level of P < 0.0001, and
2-6 times faster, with a statistical significance level of P < 0.01,
than the 2D live-wire method, and 3-15 times faster than manual
tracing. (C) 2000 Elsevier Science B.V. AU rights reserved.
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582. | Audette, MA, Ferrie, FP, and Peters, TM, "An algorithmic overview of surface registration techniques for medical imaging," MEDICAL IMAGE ANALYSIS, vol. 4, pp. 201-217, 2000.
Abstract:
This paper presents a literature survey of automatic 3D surface
registration techniques emphasizing the mathematical and algorithmic
underpinnings of the subject. The relevance of surface registration to
medical imaging is that there is much useful anatomical information in
the form of collected surface points which originate from complimentary
modalities and which must be reconciled. Surface registration can be
roughly partitioned into three issues: choice of transformation,
elaboration of surface representation and similarity criterion, and
matching and global optimization. The first issue concerns the
assumptions made about the nature of relationships between the two
modalities, e.g. whether a rigid-body assumption applies, and if nor,
what type and how general a relation optimally maps one modality onto
the other. The second issue determines what type of information we
extract from the 3D surfaces, which typically characterizes their local
or global shape, and how we organize this information into a
representation of the surface which will lead to improved efficiency
and robustness in the last stage. The last issue pertains to how we
exploit this information to estimate the transformation which best
aligns local primitives in a globally consistent manner or which
maximizes a measure of the similarity in global shape of two surfaces.
Within this framework, this paper discusses in detail each surface
registration issue and reviews the state-of-the-art among existing
techniques. (C) 2000 Elsevier Science BN. All rights reserved.
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2001 |
583. | Ferrant, M, Nabavi, A, Macq, B, Jolesz, FA, Kikinis, R, and Warfield, SK, "Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 1384-1397, 2001.
Abstract:
We present a new algorithm for the nonrigid registration of
three-dimensional magnetic resonance (MR) intraoperative image
sequences showing brain shift. The algorithm tracks key surfaces of
objects (cortical surface and the lateral ventricles) in the image
sequence using a deformable surface matching algorithm. The volumetric
deformation field of the objects is then inferred from the
displacements at the boundary surfaces using a linear elastic
biomechanical finite-element model. Two experiments on synthetic image
sequences are presented, as well as an initial experiment on
intraoperative MR images showing brain shift. The results of the
registration algorithm show a good correlation of the internal brain
structures after deformation, and a good capability of measuring
surface as well as subsurface shift. We measured distances between
landmarks in the deformed initial image and the corresponding landmarks
in the target scan. Cortical surface shifts of up to 10 min and
subsurface shifts of up to 6 mm were recovered with an accuracy of 1
nun or less and 3 min or less respectively.
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584. | Choi, WP, Lam, KM, and Siu, WC, "An adaptive active contour model for highly irregular boundaries," PATTERN RECOGNITION, vol. 34, pp. 323-331, 2001.
Abstract:
Snake is an active contour model for representing image contours. In
this paper, we propose an efficient active contour model which can
represent highly irregular boundaries. The algorithm includes an
adaptive force along the contour, and adjusts the number of points for
the snake according to the desired boundary. A better stopping
criterion based on the area of a closed contour is devised.
Furthermore, in this method, a contour can break automatically to
represent the contours of multiple objects. Experiments show that this
method can extract object's boundaries accurately and efficiently. (C)
2000 Pattern Recognition Society. Published by Elsevier Science Ltd.
All rights reserved.
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585. | Germain, O, and Refregier, P, "Edge location in SAR images: Performance of the likelihood ratio filter and accuracy improvement with an active contour approach," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 72-78, 2001.
Abstract:
The likelihood ratio edge detector is an efficient filter for the
segmentation of synthetic aperture radar (SAR) images. We show that
this filter provides biased location of the edge, when the window does
not have the same orientation as the edge. A phenomenological model is
proposed to characterize this bias. We then introduce an efficient
technique to refine edge location: the statistical active contour. The
combination of these two methods permits to achieve accurate and
regularized edge location.
|
586. | Ojala, T, Nappi, J, and Nevalainen, O, "Accurate segmentation of the breast region from digitized mammograms," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 25, pp. 47-59, 2001.
Abstract:
The segmentation of a digital mammogram into the breast region and the
background is a necessary prerequisite in computer-assisted diagnosis
of mammograms. By the exclusion of the background region, the accuracy
of the analysis is increased and the running-time is decreased. The
algorithm which segments the breast region from the background should
be fully automated and give correct results for all kinds of digitized
mammograms, including low-quality images. In this paper we present such
an algorithm based on histogram thresholding, morphological filtering
and contour modeling. Quantitative test results indicate that the
computed boundary follows the estimated boundary accurately. (C) 2000
Elsevier Science Ltd. All rights reserved.
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587. | Fornefett, M, Rohr, K, and Stiehl, HS, "Radial basis functions with compact support for elastic registration of medical images," IMAGE AND VISION COMPUTING, vol. 19, pp. 87-96, 2001.
Abstract:
Common elastic registration schemes based on landmarks and radial basis
functions (RBFs) such as thin-plate splines or multiquadrics are
global. Here, we introduce radial basis functions with compact support
for elastic registration of medical images which have an improved
locality, i.e. which allow to constrain elastic deformations to image
parts where required. We give the theoretical background of these basis
functions and compare them with other basis functions w.r.t. locality,
solvability, and efficiency. A detailed comparison with the Gaussian as
well as conditions for preserving topology is given. An important
property of the used RBFs (Wendland's psi -functions) is that they are
positive definite. Therefore, in comparison to the use of the truncated
Gaussian, the solvability of the resulting system of equations is
always guaranteed. We demonstrate the applicability of our approach for
synthetic as well as for 2D and 3D tomographic images. (C) 2001
Elsevier Science B.V. All rights reserved.
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588. | Chan, TF, and Vese, LA, "Active contours without edges," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 266-277, 2001.
Abstract:
In this paper, we propose a new model for active contours to detect
objects in a given image, based on techniques of curve evolution,
Mumford-Shah functional for segmentation and level sets. Our model can
detect objects whose boundaries are not necessarily defined by
gradient. We minimize an energy which can he seen as a particular case
of the minimal partition problem, In the level set formulation, the
problem becomes a "mean-curvature flow"-like evolving the active
contour, which will stop on the desired boundary. However, the stopping
term does not depend on the gradient of the. image, as in the classical
active contour models, hut is instead related to a particular
segmentation of the image. We will give a numerical algorithm using
finite differences. Finally, we will present various experimental
results and in particular some examples for which the classical snakes
methods based on the gradient are not applicable. Also, the initial
curve can be anywhere in the image, and interior contours are
automatically detected.
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589. | Kim, W, Lee, CY, and Lee, JJ, "Tracking moving object using Snake's jump based on image flow," MECHATRONICS, vol. 11, pp. 199-226, 2001.
Abstract:
An active contour model, Snake, was developed as a useful segmenting
and tracking tool for rigid or non-rigid (i.e, deformable) objects by
Kass in 1987. Snake is designed on the basis of Snake energies.
Segmenting and tracking can be executed successfully by the process of
energy minimization. The ability to contract is an important process
for segmenting objects from images, but the contraction forces of Kass'
Snake are dependent on the object's form. In this research, new
contraction energy, independent of the object's form, is proposed for
the better segmentation of objects. Kass' Snake can be applied to the
case of small changes between images because its solutions can be
achieved on the basis of variational approach. If a somewhat fast
moving object exists in successive images, Kass' Snake will not operate
well because the moving object may have large differences in its
position or form, between successive images. Snake's nodes may fall
into the local minima in their motion to the new positions of the
target object in next image. When the motion is too large to apply
image flow energy to tracking, a jump mode is proposed for solving the
problem. The vector used to make Snake's nodes jump to the new location
can be obtained by processing the image flow. The effectiveness of the
proposed Snake is confirmed by some simulations. (C) 2000 Published by
Elsevier Science Ltd.
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590. | Dubuisson-Jolly, MP, and Gupta, A, "Tracking deformable templates using a shortest path algorithm," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 81, pp. 26-45, 2001.
Abstract:
This paper proposes a new technique to track deformable templates. We
extend the typical graph algorithms that have been used for active
contour recovery to incorporate shape information. The advantage of
graph algorithms is that they are guaranteed to find the global minimum
of the energy function. The difficulty with their traditional use for
active contours is that they consider only two pixels at a time when
recovering the contour, making it impossible to enforce shape
constraints. We define the deformable template as a polygonal contour,
demonstrate the proper mapping between the image, the contour, and a
graph, and show how to apply Dijkstra's algorithm to track contours in
image sequences. Examples are shown for deforming contours, articulated
objects, and smooth contours being tracked in simple and complicated
backgrounds. We also provide an analysis of the computational
requirements. (C) 2001 Academic Press.
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591. | Park, H, Schoepflin, T, and Kim, Y, "Active contour model with gradient directional information: Directional snake," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol. 11, pp. 252-256, 2001.
Abstract:
Active contours or snakes are an effective edge-based method in
segmenting an object of interest, However, the segmented boundary of a
moving object in one video frame may lie far from the same moving
object in the next frame due to its rapid motion, causing the snake to
converge on the wrong edges. To guide the snake toward the appropriate
edges, we have added gradient-directional information to the external
image force to create a "directional snake." Thus, in minimizing the
snake energy, the new method considers both the gradient strength and
gradient direction of the image. Experimental results demonstrate that
the directional snake can provide a better segmentation than the
conventional method in certain situations, e.g., when there are
multiple edge candidates in the neighborhood with different directions.
The directional snake is significant because it provides a framework to
incorporate directional information in digital video segmentation.
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592. | Gotte, MJW, van Rossum, AC, Twisk, JWR, Kuijer, JPA, Marcus, JT, and Visser, CA, "Quantification of regional contractile function after infarction: Strain analysis superior to wall thickening analysis in discriminating infarct from remote myocardium," JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, vol. 37, pp. 808-817, 2001.
Abstract:
OBJECTIVES Using two-dimensional wall thickening (WT) (expressed as
percentage) and strain analysis, regional contractile myocardial
function was quantified and compared in 13 control subjects and 13
patients with a first myocardial infarction (MI). The finding in the
patient group were related to global ventricular function and infarct
size.
BACKGROUND In patients with coronary artery disease, regions with
dysfunctional myocardium cannot be differentiated easily from regions
with normal function by planar WT analysis. Physiologic factors, in
combination with limitations of conventional imaging techniques, affect
the calculation of WT. Quantitative assessment of contractile function
by magnetic resonance (MR) tissue tagging and strain analysis may be
less affected by these factors.
METHODS Two-dimensional regional WT and strain were calculated in three
short-axis MR cine and ragged images, respectively. Left ventricular
volumes and ejection fraction (EF) were obtained from a series of
contiguous short-axis cine images.
RESULTS In patients with infarct-related ventricles, WT and strain
analysis both revealed reduced myocardial function, as compared with
control subjects (p < 0.005 and p < 0.001, respectively). However, WT
analysis yielded no significant regional differences in function
between infarct-related and remote myocardium (p = 0.064), whereas
strain analysis did (p < 0.005). For detecting dysfunctional myocardium
of electrocardiographically and angiographically defined infarct areas,
WT analysis had a sensitivity of 69% and a specificity of 92%, whereas
strain analysis demonstrated a sensitivity of 92% and a specificity of
99%. The EF correlated with WT (r = 0.76, p < 0.005) and strain (r =
0.89, p < 0.001).
CONCLUISONS Two-dimensional strain analysis is more accurate than
planar WT analysis in discriminating dysfunctional from functional
myocardium, and it provides a strong correlation between regional
myocardial and global ventricular function. (J Am Coil Cardiol 2001;37:
808-17) (C) 2001 by the American College of Cardiology.
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593. | Abu-Gharbieh, R, Hamarneh, G, Gustavsson, T, and Kaminski, CF, "Flame front tracking by laser induced fluorescence spectroscopy and advanced image analysis," OPTICS EXPRESS, vol. 8, pp. 278-287, 2001.
Abstract:
This paper presents advanced image analysis methods for extracting
information from high speed Planar Laser Induced Fluorescence (PLIF)
data obtained from turbulent ames. The application of non-linear
anisotropic diffusion filtering and of Active Contour Models ( Snakes)
is described to isolate flame boundaries. In a subsequent step, the
detected flame boundaries are tra ked in time using a frequency domain
contour interpolation scheme. The implementations of the methods are
described and possible applications of the techniques are discussed.
(C) 2001 Optical Society of America.
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594. | Inglis, IM, and Gray, AJ, "An evaluation of semiautomatic approaches to contour segmentation applied to fungal hyphae," BIOMETRICS, vol. 57, pp. 232-239, 2001.
Abstract:
Semiautomatic image analysis techniques are particularly useful in
biological applications, which commonly generate very complex images,
and offer considerable flexibility. However, systematic study of such
methods is lacking; most research develops fully automatic algorithms.
This paper describes a study to evaluate several different
semiautomatic or computer-assisted approaches to contour segmentation
within the context of segmenting degraded images of fungal hyphae. Four
different types of contour segmentation method, with varying degrees
and types of user input, are outlined and applied to hyphal images. The
methods are evaluated both quantitatively and qualitatively by
comparing results obtained by several test subjects segmenting
simulated images qualitatively similar to the hyphal images of
interest. An active contour model approach, using control points,
emerges as the method to be preferred to three more traditional
approaches. Feedback from the image provider indicates that any of the
methods described have something useful to offer for segmentation of
hyphae.
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595. | Mignotte, M, and Meunier, J, "A multiscale optimization approach for the dynamic contour-based boundary detection issue," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 25, pp. 265-275, 2001.
Abstract:
We present a new multiscale approach for deformable contour
optimization. The method relies on a multigrid minimization method and
a coarse-to-fine relaxation algorithm. This approach consists in
minimizing a cascade of optimization problems of reduced and increasing
complexity instead of considering the minimization problem on the full
and original configuration space. Contrary to classical multiresolution
algorithms, no reduction of image is applied. The family of defined
energy functions are derived from the original (full resolution)
objective function, ensuring that the same function is handled at each
scale and that the energy decreases at each step of the deformable
contour minimization process. The efficiency and the speed of this
multiscale optimization strategy is demonstrated in the difficult
context of the minimization of a region-based contour energy function
ensuring the boundary detection of anatomical structures in ultrasound
medical imagery. In this context, the proposed multiscale segmentation
method is compared to other classical region-based segmentation
approaches such as Maximum Likelihood or Markov Random Field-based
segmentation techniques. We also extend this multiscale segmentation
strategy to active contour models using a classical edge-based
likelihood approach. Finally, time and performance analysis of this
approach, compared to the (commonly used) dynamic programming-based
optimization procedure, is given and allows to attest the accuracy and
the speed of the proposed method. (C) 2001 Elsevier Science Ltd. All
rights reserved.
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596. | Frangi, AF, Niessen, WJ, and Viergever, MA, "Three-dimensional modeling for functional analysis of cardiac images: A review," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 2-25, 2001.
Abstract:
Three-dimensional (3-D) imaging of the heart is a rapidly del eloping
area of research in medical imaging, Advances in hardware and methods
for fast spatio-temporal cardiac imaging are extending the frontiers of
clinical diagnosis and research on cardiovascular diseases.
In the last few Sears, many approaches hare been proposed to analyze
images and extract parameters of cardiac shape and function from a
variety of cardiac imaging modalities. In particular, techniques based
on spatio-temporal geometric models have received considerable
attention. This paper surveys the literature of tno decades of research
on cardiac modeling. The contribution of the paper is three-fold: 1) to
serve as a tutorial of the field for both clinicians and technologists,
2) to provide an extensive account of modeling techniques in a
comprehensive and systematic manner, and 3) to critically review these
approaches in terms of their performance and degree of clinical
evaluation with respect to the final goal of cardiac functional
analysis, From this review it is concluded that whereas 3-D model-based
approaches have the capability. to improve the diagnostic value of
cardiac images, issues as robustness, 3-D interaction, computational
complexity and clinical validation still require significant attention.
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597. | Yabuki, N, Matsuda, Y, Ota, M, Sumi, Y, Fukui, Y, and Miki, S, "Improvement of active net model for region detection in an image," IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, vol. E84A, pp. 720-726, 2001.
Abstract:
Processes in image recognition include target detection and shape
extraction. Active Net has been proposed as one of the methods for such
processing. It treats the target detection in all image as an energy
optimization problem. In this paper. a problem of the conventional
Active Net is presented and the new Active Net is proposed. The new net
is improved the ability for detecting a target. Finally, the validity
of the proposed net is confirmed by experimental results.
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598. | Heller, EN, Staib, LH, Dione, DP, Constable, RT, Shi, CQX, Duncan, JS, and Sinusas, AJ, "A new method for quantification of spatial and temporal parameters of endocardial motion: Evaluation of experimental infarction using magnetic resonance imaging," CANADIAN JOURNAL OF CARDIOLOGY, vol. 17, pp. 309-318, 2001.
Abstract:
BACKGROUND: With the development of high-resolution myocardial imaging
there has evolved a need for automated techniques that can accurately
quantify regional function.
OBJECTIVE: To develop a new method for quantification of spatial and
temporal parameters of endocardial motion.
DESIGN: Magnetic resonance images were analyzed using a unique,
shape-based approach that tracks endocardial surface motion at defined
points through the cardiac cycle by minimizing the bending energy.
SETTING: Animal instrumentation was performed in the Nuclear Cardiology
Experimental Research Laboratory at Yale University, New Haven,
Connecticut. Magnetic resonance imaging was performed at the Yale New
Haven Hospital Center.
ANIMALS: Eight mongrel canines were used.
INTERVENTIONS: Electrocardiograph gated, gradient-echo magnetic
resonance images were obtained before and after occlusion of the left
anterior descending coronary artery. Thirty-two points along
automatically defined endocardial contours were tracked. Average
displacements and cumulative path lengths were computed from
end-diastole for each point over the entire cardiac cycle. The average
cumulative path length was computed for each of four quarters of
systole for the normal, border and infarct zones. Shape-based
parameters of systolic motion were compared with the centreline
approach. Infarct zone was defined by postmortem histochemical staining.
MAIN RESULTS: Displacement and cumulative path length over the cardiac
cycle decreased significantly in the infarct and border zones (P<0.05),
but did not change in the normal zone (P was not significant). Temporal
changes in motion were observed in all zones. Displacement measured
using the shape based algorithm was more consistent than cumulative
path length when compared with systolic motion measured using the
centreline method.
CONCLUSIONS: An automated, shape-based approach permits quantitative
evaluation of both spatial and temporal parameters of regional
endocardial motion from high-resolution electrocardiograph gated
images. Analysis of endocardial motion and cumulative motion over the
entire cardiac cycle discriminated infarcted from normal and border
regions.
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599. | De Solorzano, CO, Malladi, R, Lelievre, SA, and Lockett, SJ, "Segmentation of nuclei and cells using membrane related protein markers," JOURNAL OF MICROSCOPY-OXFORD, vol. 201, pp. 404-415, 2001.
Abstract:
Segmenting individual cell nuclei from microscope images normally
involves volume labelling of the nuclei with a DNA stain. However, this
method often fails when the nuclei are tightly clustered in the tissue,
because there is little evidence from the images on where the borders
of the nuclei are. In this paper we present a method which solves this
limitation and furthermore enables segmentation of whole cells. Instead
of using volume stains, we used stains that specifically label the
surface of nuclei or cells: lamins for the nuclear envelope and alpha-6
or beta-1 integrins for the cellular surface. The segmentation is
performed by identifying unique seeds for each nucleus/cell and
expanding the boundaries of the seeds until they reach the limits of
the nucleus/cell, as delimited by the lamin or integrin staining, using
gradient-curvature flow techniques. We tested the algorithm using
computer-generated objects to evaluate its robustness against noise and
applied it to cells in culture and to tissue specimens. In all the
cases that we present the algorithm gave accurate results.
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600. | Little, JJ, and Shi, P, "Structural lines, TINs, and DEMs," ALGORITHMICA, vol. 30, pp. 243-263, 2001.
Abstract:
The standard method of building compact triangulated surface
approximations to terrain surfaces (TINs) from dense digital elevation
models (DEMs) adds points to an initial sparse triangulation or removes
points from a dense initial mesh. Instead, we find structural lines to
act as the initial skeleton of the triangulation. These lines are based
on local curvature of the surface, not on the Row of water. We build
TINs from DEMs with points and structural lines. These experiments show
that initializing the TIN with structural lines at the correct scale
creates a TIN with fewer points given a particular approximation error.
Structural lines are especially effective for small numbers of points
and correspondingly rougher approximations.
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601. | Shearer, K, Wong, KD, and Venkatesh, S, "Combining multiple tracking algorithms for improved general performance," PATTERN RECOGNITION, vol. 34, pp. 1257-1269, 2001.
Abstract:
Automated tracking of objects through a sequence of images has remained
one of the difficult problems in computer vision. Numerous algorithms
and techniques have been proposed for this task. Some algorithms
perform well in restricted environments, such as tracking using
stationary camel as, but a general solution is not currently available.
A frequent problem is that when an algorithm is refined for one
application, it becomes unsuitable for other applications, This paper
proposes a general tracking system based on a different approach.
Rather than refine one algorithm for a specific tracking task, two
tracking algorithms are employed, and used to correct each other during
the tracking task. By choosing the two algorithms such that they have
complementary failure modes, a robust algorithm is created without
increased specialisation. (C) 2001 Pattern Recognition Society.
Published by Elsevier Science Ltd. All rights reserved.
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602. | Zahalka, A, and Fenster, A, "An automated segmentation method for three-dimensional carotid ultrasound images," PHYSICS IN MEDICINE AND BIOLOGY, vol. 46, pp. 1321-1342, 2001.
Abstract:
We have developed an automated segmentation method for
three-dimensional vascular ultrasound images. The method consists of
two steps: an automated initial contour identification, followed by
application of a geometrically deformable model (GDM). The formation of
the initial contours requires the input of a single seed point by the
user, and was shown to be insensitive to the placement of the seed
within a structure. The GDM minimizes contour energy, providing a
smoothed final result. It requires only three simple parameters, all
with easily selectable values. The algorithm is fast, performing
segmentation on a 336 x 352 x 200 volume in 25 s when running on a 100
MHz 9500 Power Macintosh prototype. The segmentation algorithm was
tested on stenosed vessel phantoms with known geometry, and the
segmentation of the cross-sectional areas was found to be within 3% of
the true area. The algorithm was also applied to two sets of patient
carotid images, one acquired with a mechanical scanner and the other
with a freehand scanning system, with good results on both.
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603. | Pardo, XM, Carreira, MJ, Mosquera, A, and Cabello, D, "A snake for CT image segmentation integrating region and edge information," IMAGE AND VISION COMPUTING, vol. 19, pp. 461-475, 2001.
Abstract:
The 3D representation and solid modeling of knee bone structures taken
from computed tomography (CT) scans are necessary processes in many
medical applications. The construction of the 3D model is generally
carried out by stacking the contours obtained from a 2D segmentation of
each CT slice, so the quality of the 3D model strongly depends on the
precision of this segmentation process. In this work we present a
deformable contour method for the problem of automatically delineating
the external bone (tibia and fibula) contours from a set of CT scan
images. We have introduced a new region potential term and an edge
focusing strategy that diminish the problems that the classical snake
method presents when it is applied to the segmentation of CT images. We
introduce knowledge about the location of the object of interest and
knowledge about the behavior of edges in scale space, in order to
enhance edge information. We also introduce a region information aimed
at complementing edge information. The novelty in that is that the new
region potential does not rely on prior knowledge about image
statistics; the desired features are derived from the segmentation in
the previous slice of the 3D sequence. Finally, we show examples of 3D
reconstruction demonstrating the validity of our model. The performance
of our method was visually and quantitatively validated by experts. (C)
2001 Elsevier Science B.V. All rights reserved.
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604. | Francois, ARJ, and Medioni, GG, "Interactive 3D model extraction from a single image," IMAGE AND VISION COMPUTING, vol. 19, pp. 317-328, 2001.
Abstract:
We present a system at the junction between Computer Vision and
Computer Graphics, to produce a three-dimensional (3D) model of an
object as observed in a single image, with a minimum of high-level
interaction from a user.
The input to our system is a single image. First, the user points,
coarsely, at image features (edges) that are subsequently automatically
and reproducibly extracted in real-time. The user then performs a high
level labeling of the curves (e.g. limb edge, cross-section) and
specifies relations between edges (e.g. symmetry, surface or part).
NURBS are used as working representation of image edges. The objects
described by the user specified, qualitative relationships are then
reconstructed either as a set of connected parts modeled as Generalized
Cylinders, or as a set of 3D surfaces for 3D bilateral symmetric
objects. In both cases, the texture is also extracted from the image.
Our system runs in realtime on a PC. (C) 2001 Elsevier Science B.V. All
rights reserved.
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605. | Doucette, P, Agouris, P, Stefanidis, A, and Musavi, M, "Self-organised clustering for road extraction in classified imagery," ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol. 55, pp. 347-358, 2001.
Abstract:
The extraction of road networks from digital imagery is a fundamental
image analysis operation. Common problems encountered in automated road
extraction include high sensitivity to typical scene clutter in
high-resolution imagery, and inefficiency to meaningfully exploit
multispectral imagery (MSI). With a ground sample distance (GSD) of
less than 2 m per pixel, roads can be broadly described as elongated
regions. We propose an approach of elongated region-based analysis for
2D road extraction from high-resolution imagery, which is suitable for
MSI, and is insensitive to conventional edge definition. A
self-organising road map (SORM) algorithm is presented. inspired from a
specialised variation of Kohonens self-organising map (SOM) neural
network algorithm. A spectrally classified high-resolution image is
assumed to be the input for our analysis. Our approach proceeds by
performing spatial cluster analysis as a mid-level processing
technique. This allows us to improve tolerance to road clutter in
high-resolution images, and to minimise the effect on road extraction
of common classification errors. This approach is designed in
consideration of the emerging trend towards high-resolution
multispectral sensors. Preliminary results demonstrate robust road
extraction ability due to the non-local approach, when presented with
noisy input. (C) 2001 Elsevier Science B.V. All rights reserved.
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606. | Ballerini, L, "Genetic snakes for color images segmentation," APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 2037, pp. 268-277, 2001.
Abstract:
The world of meat faces a permanent need for new methods of meat
quality evaluation. Recent advances in the area of computer and video
processing have created new ways to monitor quality in the food
industry. In this paper we propose a segmentation method to separate
connective tissue from meat. We propose the use of Genetic Snakes, that
are active contour models, also known as snakes, with an energy
minimization procedure based on Genetic Algorithms (GA). Genetic Snakes
have been proposed to overcome some limits of the classical snakes, as
initialization, existence of multiple minima, and the selection of
elasticity parameters, and have both successfully applied to medical
and radar images. We extend the formulation of Genetic Snakes in two
ways, by exploring additional internal and external energy terms and by
applying them to color images. We employ a modified version of the
image energy which considers the gradient of the three color RGB (red,
green and blue) components. Experimental results on synthetic images as
well as on meat images are reported. Images used in this work are color
camera photographs of beef meat.
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607. | Tao, CV, Chapman, MA, and Chaplin, BA, "Automated processing of mobile mapping image sequences," ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol. 55, pp. 330-346, 2001.
Abstract:
Automated approaches to image sequence processing using mobile mapping
imagery have been under investigation in the Department of Geomatics
Engineering at The University of Calgary. This paper presents an
overview of several methods developed for the VISAT (TM) mobile mapping
system at The University of Calgary. Following a brief overview of
mobile mapping technology, an analysis of mobile mapping image
sequences from the viewpoint of visual motion theory is provided.
Particular attention is paid to image and object domain constraints
that can be exploited in the processing of mobile mapping image
sequences. Several key methods to automated processing of mobile
mapping image sequences are then described. These methods can be
grouped into two categories, namely, information extraction and
image-based trajectory determination (bridging). (C) 2001 Elsevier
Science B.V. All rights reserved.
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608. | Chen, YM, and Bose, P, "On the incorporation of time-delay regularization into curvature-based diffusion," JOURNAL OF MATHEMATICAL IMAGING AND VISION, vol. 14, pp. 149-164, 2001.
Abstract:
A new anisotropic nonlinear diffusion model incorporating time-delay
regularization into curvature-based diffusion is proposed for image
restoration and edge detection. A detailed mathematical analysis of the
proposed model in the form of the proof of existence, uniqueness and
stability of the "viscosity" solution of the model is presented.
Furthermore, implementation issues and computational methods for the
proposed model are also discussed in detail. The results obtained from
testing our denoising and edge detection algorithm on several synthetic
and real images showed the effectiveness of the proposed model in
prserving sharp edges and fine structures while removing noise.
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609. | Shen, DG, Herskovits, EH, and Davatzikos, C, "An adaptive-focus statistical shape model for segmentation and shape modeling of 3-D brain structures," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 257-270, 2001.
Abstract:
This paper presents a deformable model for automatically segmenting
brain structures from volumetric magnetic resonance (MR) images and
obtaining point correspondences, using geometric and statistical
information in a hierarchical scheme. Geometric information is embedded
into the model via a set of affine-invariant attribute vectors, each of
which characterizes the geometric structure around a point of the model
from a local to a global scale, The attribute vectors, in conjunction
with the deformation mechanism of the model, warranty that the model
not only deforms to nearby edges, as is customary in most deformable
surface models, but also that it determines point correspondences based
on geometric similarity at different scales. The proposed model is
adaptive in that it initially focuses on the most reliable structures
of interest, and gradually shifts focus to other structures as those
become closer to their respective targets and, therefore, more
reliable. The proposed techniques have been used to segment boundaries
of the ventricles, the caudate nucleus, and the lenticular nucleus from
volumetric MR images.
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610. | Sclaroff, S, and Liu, LF, "Deformable shape detection and description via model-based region grouping," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 23, pp. 475-489, 2001.
Abstract:
A method for deformable shape detection and recognition is described.
Deformable shape templates are used to partition the image into a
globally consistent interpretation, determined in part by the minimum
description length principle. Statistical shape models enforce the
prior probabilities on global, parametric deformations for each object
class. Once trained, the system autonomously segments deformed shapes
from the background, while not merging them with adjacent objects or
shadows. The formulation can be used to group image regions obtained
via any region segmentation algorithm, e.g., texture. color, or motion.
The recovered shape models can be used directly in object recognition.
Experiments with color imagery are reported.
|
611. | Bajaj, CL, and Xu, GL, "Regular algebraic curve segments (III) - applications in interactive design and data fitting," COMPUTER AIDED GEOMETRIC DESIGN, vol. 18, pp. 149-173, 2001.
Abstract:
In this paper (part three of the trilogy) we use low degree G(1) and
G(2) continuous regular algebraic spline curves defined within
parallelograms, to interpolate an ordered set of data points in the
plane. We explicitly characterize curve families whose members have the
required interpolating properties and possess a minimal number of
inflection points. The regular algebraic spline curves considered here
have many attractive features: They are easy to construct. There exist
convenient geometric control handles to locally modify the shape of the
curve. The error of the approximation is controllable. Since the spline
curve is always inside the parallelogram, the error of the fit is
bounded by the size of the parallelogram. The spline curve can be
rapidly displayed, even though the algebraic curve segments are
implicitly defined. (C) 2001 Elsevier Science B.V. All rights reserved.
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612. | Lehmann, TM, Bredno, J, Metzler, V, Brook, G, and Nacimiento, W, "Computer-assisted quantification of axo-somatic boutons at the cell membrane of motoneurons," IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 48, pp. 706-717, 2001.
Abstract:
This paper presents a system for computer-assisted quantification of
axe-somatic boutons at motoneuron cell-surface membranes, Different
immunohistochemical stains can be used to prepare tissue of the spinal
cord. Based on micrographs displaying single neurons, a finite element
balloon model has been applied to determine the exact location of the
cell membrane, A synaptic profile is extracted next to the cell
membrane and normalized with reference to the intracellular brightness.
Furthermore, a manually selected reference cell is used to normalize
settings of the microscope as well as variations in histochemical
processing for each stain. Thereafter, staining, homogeneity, and
allocation of boutons are determined automatically from the synaptic
profiles. The system is evaluated by applying the coefficient of
variation (C-v) to repeated measurements of a quantity. Based on 1856
motoneuronal images acquired from four animals with three stains, 93%
of the images are analyzed correctly. The others were rejected, based
on process protocols. Using only rabbit anti-synaptophysin as primary
antibody, the correctness increases above 96%, C-v values are below 3%,
5%, and 6% for all measures with respect to stochastic optimization,
cell positioning, and a large range of microscope settings,
respectively, A sample size of about 100 is required to validate a
significant reduction of staining in motoneurons below a hemi-section
(Wilcoxon rank-sum test, alpha = 0.05, beta = 0.9), Our system yields
statistically robust results from light micrographs. In future, it is
hoped that this system will substitute for the expensive and
time-consuming analysis of spinal cord injury at the ultra-structural
level, such as by manual interpretation of nonoverlapping electron
micrographs.
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613. | Asano, T, Chen, DZ, Katoh, N, and Tokuyama, T, "Efficient algorithms for optimization-based image segmentation," INTERNATIONAL JOURNAL OF COMPUTATIONAL GEOMETRY & APPLICATIONS, vol. 11, pp. 145-166, 2001.
Abstract:
Separating an object in an image from its background is a central
problem (called segmentation) in pattern recognition and computer
vision. In this paper, we study the computational complexity of the
segmentation problem, assuming that the sought object forms a connected
region in an intensity image. We show that the optimization problem of
separating a connected region in a grid of M x N pixels is NP-hard
under the interclass variance, a criterion that is often used in
discriminant analysis. More importantly, we consider the basic case in
which the object is bounded by two x-monotone curves (i.e., the object
itself is x-monotone), and present polynomial-time algorithms for
computing the optimal segmentation. Our main algorithm for exact
optimal segmentation by two x-monotone curves runs in O(N-4) time; this
algorithm is based on several techniques such as a parametric
optimization formulation, a hand-probing algorithm for the convex hull
of an unknown planar point set, and dynamic programming using fast
matrix searching. Our efficient approximation scheme obtains an epsilon
-approximate solution in O(epsilon N--1(2) log L) time, where epsilon
is any fixed constant with 1 > epsilon > 0, and L is the total sum of
the absolute values of the brightness levels of the image.
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614. | Firbank, MJ, Harrison, RM, Williams, ED, and Coulthard, A, "Measuring extraocular muscle volume using dynamic contours," MAGNETIC RESONANCE IMAGING, vol. 19, pp. 257-265, 2001.
Abstract:
The effect of medical treatment on extraocular muscle enlargement in
thyroid associated ophthalmopathy (TAO) may be monitored by measuring
the change in volume of the extraocular muscles on serial orbital MRI
examinations. In theory. 3D image sets offer the opportunity to
minimise errors due to poor repositioning and partial volume effects.
This study describes an automated technique for estimating extraocular
muscle volumes from 3D datasets. Operator input is minimal and the
technique is robust. Verification of the technique on both simulated
and real datasets is described. For simulated image sets, both
automated segmentation and manual outlining produced estimates of
volume which were on average 4% less than 'true' volume. For real
patient data, extraocular muscle volumes measured by the automated
technique were 1.6% (SD 13%) less than volumes measured by manual
outlining. Coefficient of variation for repeat outlining of the same
image dataset for the automated technique was 1.0%, compared with 4%
for manual outlining. The manual technique took an experienced operator
approximately 20 min to perform. compared to 7 min fur the automated
technique. The automated method is therefore rapid, reproducible and at
least as accurate as other available methods. (C) 2001 Elsevier Science
Inc. All rights reserved.
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615. | Lie, WN, and Chuang, CH, "Fast and accurate snake model for object contour detection," ELECTRONICS LETTERS, vol. 37, pp. 624-626, 2001.
Abstract:
A new scheme in which a snake model is used fnr object contour
detection is proposed. By developing a no-search movement scheme,
accepting the effective gradient vector flow field as the contracting
force, and adjusting the weighting parameters automatically, an
algorithm that is fast, less sensitive to initial contour conditions
and accurate in approaching concave parts of an object boundary is
obtained.
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616. | Desolneux, A, Moisan, L, and Morel, JM, "Edge detection by Helmholtz principle," JOURNAL OF MATHEMATICAL IMAGING AND VISION, vol. 14, pp. 271-284, 2001.
Abstract:
We apply to edge detection a recently introduced method for computing
geometric structures in a digital image, without any a priori
information. According to a basic principle of perception due to
Helmholtz, an observed geometric structure is perceptually "meaningful"
if its number of occurences would be very small in a random situation:
in this context, geometric structures are characterized as large
deviations from randomness. This leads us to define and compute edges
and boundaries (closed edges) in an image by a parameter-free method.
Maximal detectable boundaries and edges are defined, computed, and the
results compared with the ones obtained by classical algorithms.
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617. | Cohen, LD, "Multiple contour finding and perceptual grouping using minimal paths," JOURNAL OF MATHEMATICAL IMAGING AND VISION, vol. 14, pp. 225-236, 2001.
Abstract:
We address the problem of finding a set of contour curves in an image.
We consider the problem of perceptual grouping and contour completion,
where the data is a set of points in the image. A new method to find
complete curves from a set of contours or edge points is presented. Our
approach is based on a previous work on finding contours as minimal
paths between two end points using the fast marching algorithm (L. D
Cohen and R. Kimmel, International Journal of Computer Vision, Vol. 24,
No. 1, pp. 57-78, 1997). Given a set of key points, we find the pairs
of points that have to be linked and the paths that join them. We use
the saddle points of the minimal action map. The paths are obtained by
backpropagation from the saddle points to both points of each pair.
In a second part, we propose a scheme that does not need key points for
initialization. A set of key points is automatically selected from a
larger set of admissible points. At the same time, saddle points
between pairs of key points are extracted. Next, paths are drawn on the
image and give the minimal paths between selected pairs of points. The
set of minimal paths completes the initial set of contours and allows
to close them. We illustrate the capability of our approach to close
contours with examples on various images of sets of edge points of
shapes with missing contours.
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618. | Coleman, TF, Li, YY, and Mariano, A, "Segmentation of pulmonary nodule images using 1-norm minimization," COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, vol. 19, pp. 243-272, 2001.
Abstract:
Total variation minimization (in the 1-norm) has edge preserving and
enhancing properties which make it suitable for image segmentation. We
present Image Simplification, a new formulation and algorithm for image
segmentation. We illustrate the edge enhancing properties of 1-norm
total variation minimization in a discrete setting by giving exact
solutions to the problem for piecewise constant functions in the
presence of noise. In this case, edges can be exactly recovered if the
noise is sufficiently small. After optimization, segmentation is
completed using edge detection. We find that our image segmentation
approach yields good results when applied to the segmentation of
pulmonary nodules.
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619. | Park, JY, McInerney, T, Terzopoulos, D, and Kim, MH, "A non-self-intersecting adaptive deformable surface for complex boundary extraction from volumetric images," COMPUTERS & GRAPHICS-UK, vol. 25, pp. 421-440, 2001.
Abstract:
This paper proposes a non-self-intersecting multiscale deformable
surface model with an adaptive remeshing capability. The model is
specifically designed to extract the three-dimensional boundaries of
topologically simple but geometrically complex anatomical structures,
especially those with deep concavities such as the brain, from
volumetric medical images. The model successfully addresses three
significant problems of conventional deformable models when dealing
with such structures-sensitivity to model initialization, difficulties
in dealing with severe object concavities, and model self-intersection.
The first problem is addressed using a multiscale scheme, which
extracts the boundaries of objects in a coarse-to-fine fashion by
applying a multiscale deformable surface model to a multiresolution
volume image pyramid. The second problem is addressed with adaptive
remeshing, which progressively resamples the triangulated deformable
surface model both globally and locally, matching its resolution to the
levels of the volume image pyramid. Finally, the third problem is
solved by including a non-self-intersection force among the customary
internal and external forces in a physics-based model formulation. Our
deformable surface model is more efficient, much less sensitive to
initialization and spurious image features, more proficient in
extracting boundary concavities, and not susceptible to
self-intersections compared to most other models of its type. This
paper presents results of applying our new deformable surface model to
the extraction of a spherical surface with concavities from a
computer-generated volume image and a brain cortical surface from a
real MR volume image. (C) 2001 Elsevier Science Ltd. All rights
reserved.
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620. | Lin, IJ, and Kung, SY, "Extraction of video objects via surface optimization and Voronoi order," JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, vol. 29, pp. 23-39, 2001.
Abstract:
We implement a video object segmentation system that integrates the
novel concept of Voronoi Order with existing surface optimization
techniques to support the MPEG-4 functionality of object-addressable
video content in the form of video objects. The major enabling
technology for the MPEG-4 standard are systems that compute video
object segmentation, i.e., the extraction of video objects from a given
video sequence. Our surface optimization formulation describes the
video object segmentation problem in the form of an energy function
that integrates many visual processing techniques. By optimizing this
surface, we balance visual information against predictions of models
with a priori information and extract video objects from a video
sequence. Since the global optimization of such an energy function is
still an open problem, we use Voronoi Order to decompose our
formulation into a tractable optimization via dynamic programming
within an iterative framework. In conclusion, we show the results of
the system on the MPEG-4 test sequences, introduce a novel objective
measure, and compare results against those that are hand-segmented by
the MPEG-4 committee.
|
621. | Ladak, HM, Thomas, JB, Mitchell, JR, Rutt, BK, and Steinman, DA, "A semi-automatic technique for measurement of arterial wall from black blood MRI," MEDICAL PHYSICS, vol. 28, pp. 1098-1107, 2001.
Abstract:
Black blood magnetic resonance imaging (MRI) has become a popular
technique fur imaging the artery wall in vivo. Its noninvasiveness and
high resolution make it ideal for studying the progression of early
atherosclerosis in normal volunteers or asymptomatic patients with mild
disease, However, the operator variability inherent in the manual
measurement of vessel wall area from MR images hinders the reliable
detection of relatively small changes in the artery wall over time. In
this paper we present a semi-automatic method for segmenting the inner
and outer boundary of the artery wall, and evaluate its operator
variability using analysis of variance (ANOVA). In our approach, a
discrete dynamic contour is approximately initialized by an operator,
deformed to the inner boundary, dilated, and then deformed to the outer
boundary. A group of four operators performed repeated measurements on
12 images from normal human subjects using both our semiautomatic
technique and a manual approach. Results from the ANOVA indicate that
the inter-operator standard error of measurement (SEM) of total wall
area decreased from 3.254 mm(2) (manual) to 1.293 mm(2) (semi
automatic), and the intra-operator SEM decreased from 3.005 mm(2) to
0.958 mm(2). Operator reliability coefficients increased fi om less
than 69% to more than 91% tinter-operator) and 95% (intra-operator).
The minimum detectable change in wall area improved from more than 8.32
mm(2) (intra-operator, manual) to less than 3.59 mm(2) tinter-operator,
semiautomatic), suggesting that it is better to have multiple operators
measure wall area with our semi-automatic technique than to have a
single operator make repeated measurements manually. Similar
improvements in wall thickness and lumen radius measurements were also
recorded. Since the semi-automatic technique has effectively ruled out
the effect. of the operator on these measurements, it may be possible
to use such techniques to expand prospective studies of atherogenesis
to multiple centers so as to increase access to real patient data
without sacrificing reliability. (C) 2001 American Association of
Physicists in Medicine.
|
622. | Ruch, O, and Refregier, P, "Minimal-complexity segmentation with a polygonal snake adapted to different optical noise models," OPTICS LETTERS, vol. 26, pp. 977-979, 2001.
Abstract:
Polygonal active contours (snakes) have been used with success for
target segmentation and tracking. We propose to adapt a technique based
on the minimum description length principle to estimate the complexity
(proportional to the number of nodes) of the polygon used for the
segmentation. We demonstrate that, provided that an up-and-down
multiresolution strategy is implemented, it is possible to estimate
efficiently this number of nodes without a priori knowledge and with a
fast algorithm, leading to a segmentation criterion without free
parameters. We also show that, for polygonal-shaped objects, this new
technique leads to better results than using a simple regularization
strategy based on the smoothness of the contour. (C) 2001 Optical
Society of America.
|
623. | Saha, PK, and Udupa, JK, "Optimum image thresholding via class uncertainty and region homogeneity," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 23, pp. 689-706, 2001.
Abstract:
Thresholding is a popular image segmentation method that converts a
gray-level image into a binary image. The selection of optimum
thresholds has remained a challenge over decades. Besides being a
segmentation tool on its own, often it is also a step in many advanced
image segmentation techniques in spaces other than the image space.
Most of the thresholding methods reported to date are based on
histogram analysis using information-theoretic approaches. These
methods have not harnessed the information captured in image
morphology. Here, we introduce a novel thresholding method that
accounts for both intensity-based class uncertainty-a histogram-based
property-and region homogeneity-an image morphology-based property. A
scale-based formulation is used for region homogeneity computation. At
any threshold, intensity-based class uncertainty is computed by fitting
a Gaussian to the intensity distribution of each of the two regions
segmented at that threshold. The theory of the optimum thresholding
method is based on the postulate that objects manifest themselves with
fuzzy boundaries in any digital image acquired by an imaging device.
The main idea here is to select that threshold at which pixels with
high class uncertainty accumulate mostly around object boundaries. To
achieve this, a new threshold energy criterion is formulated using
class-uncertainty and region homogeneity such that, at any image
location, a high energy is created when both class uncertainty and
region homogeneity are high or both are low. Finally, the method
selects that threshold which corresponds to the minimum overall energy.
The method has been compared to a recently published maximum segmented
image information (MSII) method. Superiority of the proposed method was
observed both qualitatively on clinical medical images as well as
quantitatively on 250 realistic phantom images generated by adding
different degrees of blurring, noise, and background variation to real
objects segmented from clinical images.
|
624. | Mahnken, AH, Kohnen, M, Steinberg, S, Wein, BB, and Gunther, RW, "Automated image analysis of lateral lumber X-rays by a form model.," ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, vol. 173, pp. 554-557, 2001.
Abstract:
Purpose: Development of a software for fully automated image analysis
of lateral lumbar spine X-rays. Material and method: Using the concept
of active shape models, we developed a software that produces a form
model of the lumbar spine from lateral lumbar spine radiographs and
runs an automated image segmentation. This model is able to detect
lumbar vertebrae automatically after the filtering of digitized X-ray
images. The model was trained with 20 lateral lumbar spine radiographs
with no pathological findings before we evaluated the software with 30
further X-ray images which were sorted by image quality ranging from
one (best) to three (worst). There were 10 images for each quality.
Results: image recognition strongly depended on image quality. In group
one 52 and in group two 51 out of 60 vertebral bodies including the
sacrum were recognized, but in group three only 18 vertebral bodies
were properly identified. Conclusion: Fully automated and reliable
recognition of vertebral bodies from lateral spine radiographs using
the concept of active shape models is possible. The precision of this
technique is limited by the superposition of different structures.
Further improvements are necessary. Therefore standardized image
quality and enlargement of the training data set are required.
|
625. | Varekamp, C, and Hoekman, DH, "Segmentation of high-resolution InSAR data of a tropical forest using Fourier parameterized deformable models," INTERNATIONAL JOURNAL OF REMOTE SENSING, vol. 22, pp. 2339-2350, 2001.
Abstract:
Currently, tree maps are produced from field measurements that are time
consuming and expensive. Application of existing techniques based on
aerial photography is often hindered by cloud cover. This has initiated
research into the segmentation of high resolution airborne
interferometric Synthetic Aperture Radar (SAR) data for deriving tree
maps. A robust algorithm is constructed to optimally position closed
boundaries. The boundary of a tree crown will be best approximated when
at all points on the boundary, the z-coordinate image gradient is
maximum, and directed inwards orthogonal to the boundary. This property
can be expressed as the result of a line integral along the boundary.
Boundaries with a large value for the line integral are likely to be
tree crowns. This paper focuses on the search procedure and on
illustrating how smoothing can be used to prevent the search from
becoming trapped in a local optimum. The final crown detection stage is
not described in this paper but could be based on the gradient and
implemented using the above described value for the line integral.
Results of this paper indicate that a Fourier parametrization with only
three harmonics (nine parameters) can describe the shape variation in
the 2D crown projection in sufficient detail. Current ground datasets
are not suitable for obtaining detection statistics such as the
percentage of tree crowns detected and the number of false alarms.
Better ground datasets will be needed to evaluate algorithm performance
for real tree mapping situations.
|
626. | Chang, IC, and Huang, CL, "Skeleton-based walking motion analysis using hidden Markov model and active shape models," JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, vol. 17, pp. 371-403, 2001.
Abstract:
This paper proposes a skeleton-based human walking motion analysis
system which consists of three major phases. In the first phase, it
extracts the human body skeleton from the background and then obtains
the body signatures. In the second phase, it analyzes the training
sequences to generate statistical models. In the third phase, it uses
the trained models to recognize the input human motion sequence and
calculate the motion parameters. The experimental results demonstrate
how our system can recognize the motion type and describe the motion
characteristics of the image sequence. Finally, the synthesized motion
sequences are illustrated. The major contributions of this paper are:
(1) development of a skeleton-based method and use of Hidden Markov
Models (HMM) to recognize the motion type; (2) incorporation of the
Active Shape Models (ASMs) and the body structure characteristics to
generate the motion parameter curves of the human motion.
|
627. | Kiyuna, T, Kamijo, K, Yamazaki, T, Moriyama, N, and Sekiguchi, R, "Automated reconstruction of a three-dimensional brain model from magnetic resonance images," NEUROIMAGE, vol. 13, pp. S173-S173, 2001.
Abstract:
In this paper, we address two problems crucial to motion analysis: the
detection of moving objects and their localisation. Statistical and
level set approaches are adopted in formulating these problems. For the
change detection problem, the inter-frame difference is modelled by a
mixture of two zero-mean Laplacian distributions. At first, statistical
tests using criteria with negligible error probability are used for
labelling as changed or unchanged as many sites as possible. All the
connected components of the labelled sites are used thereafter as
region seeds, which give the initial level sets for which velocity
fields for label propagation are provided, We introduce a new
multi-label fast marching algorithm for expanding competitive regions.
The solution of the localisation problem is based on the map of changed
pixels previously extracted. The boundary of the moving object is
determined by a level set algorithm, which is initialised by two curves
evolving in converging opposite directions. The sites of curve contact
determine the position of the object boundary. Experimental results
using real video sequences are presented, illustrating the efficiency
of the proposed approach. (C) 2001 Elsevier Science B.V. All rights
reserved.
|
628. | Sifakis, E, and Tziritas, G, "Moving object localisation using a multi-label fast marching algorithm," SIGNAL PROCESSING-IMAGE COMMUNICATION, vol. 16, pp. 963-976, 2001.
Abstract:
In this paper, we address two problems crucial to motion analysis: the
detection of moving objects and their localisation. Statistical and
level set approaches are adopted in formulating these problems. For the
change detection problem, the inter-frame difference is modelled by a
mixture of two zero-mean Laplacian distributions. At first, statistical
tests using criteria with negligible error probability are used for
labelling as changed or unchanged as many sites as possible. All the
connected components of the labelled sites are used thereafter as
region seeds, which give the initial level sets for which velocity
fields for label propagation are provided, We introduce a new
multi-label fast marching algorithm for expanding competitive regions.
The solution of the localisation problem is based on the map of changed
pixels previously extracted. The boundary of the moving object is
determined by a level set algorithm, which is initialised by two curves
evolving in converging opposite directions. The sites of curve contact
determine the position of the object boundary. Experimental results
using real video sequences are presented, illustrating the efficiency
of the proposed approach. (C) 2001 Elsevier Science B.V. All rights
reserved.
|
629. | Suri, JS, "Two-dimensional fast magnetic resonance brain segmentation," IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE, vol. 20, pp. 84-95, 2001.
Abstract:
This study quantifies variance components of two-dimensional strains in
the left-ventricular heart wall assessed by magnetic resonance (MR)
tagging in 18 healthy xxvolunteers. For a 7-mm tagging grid and
homogeneous strain analysis, the intersubject variability and
measurement error were estimated, as well as the intra- and
interobserver variability. The variance components were calculated for
the mean strain of a circumferential sector. The results show that the
measurement error was almost equal to the intra-observer variability.
With four circumferential sectors of 90 degrees each, approximately 65%
of the total variance in epsilon (r) and epsilon (c) was due to
intersubject variability, the remaining 35% was due to measurement
error. With 12 sectors of 30 degrees each, the intersubject variability
and measurement error both contributed 50% to the total variance. With
18 sectors of 20 degrees each, only 40% of the total variance was due
to intersubject variability. The total variability increased with the
number of sectors and therefore the number of sectors used in a study
will be a trade-off between segment size (defining spatial resolution)
and variability.
|
630. | Kuijer, JPA, Marcus, JT, Gotte, MJW, van Rossum, AC, Ader, HJ, and Heethaar, RM, "Variance components of two-dimensional strain parameters in the left-ventricular heart wall obtained by magnetic resonance tagging," INTERNATIONAL JOURNAL OF CARDIAC IMAGING, vol. 17, pp. 49-60, 2001.
Abstract:
This study quantifies variance components of two-dimensional strains in
the left-ventricular heart wall assessed by magnetic resonance (MR)
tagging in 18 healthy xxvolunteers. For a 7-mm tagging grid and
homogeneous strain analysis, the intersubject variability and
measurement error were estimated, as well as the intra- and
interobserver variability. The variance components were calculated for
the mean strain of a circumferential sector. The results show that the
measurement error was almost equal to the intra-observer variability.
With four circumferential sectors of 90 degrees each, approximately 65%
of the total variance in epsilon (r) and epsilon (c) was due to
intersubject variability, the remaining 35% was due to measurement
error. With 12 sectors of 30 degrees each, the intersubject variability
and measurement error both contributed 50% to the total variance. With
18 sectors of 20 degrees each, only 40% of the total variance was due
to intersubject variability. The total variability increased with the
number of sectors and therefore the number of sectors used in a study
will be a trade-off between segment size (defining spatial resolution)
and variability.
|
631. | Ravhon, R, Adam, D, and Zelmanovitch, L, "Validation of ultrasonic image boundary recognition in abdominal aortic aneurysm," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 751-763, 2001.
Abstract:
An aneurysm of the abdominal aorta (AAA) is characterized by modified
wall properties, and a balloon-like area usually filled by a thrombus.
A rupture of an aortic aneurysm can be fatal, yet there is no way to
accurately predict such an occurrence. The study of the wall and
thrombus cross-sectional distension, due to a pressure wave, is
important as a way of assessing the degradation of the mechanical
properties of the vessel wall and the risk of a rupture. Echo
ultrasound transverse cross-sectional imaging is used here to study the
thrombus and the aortic wall distension, requiring their segmentation
within the image. Polar coordinates are defined, and a search is
performed for minimizing a cost function, which includes a description
of the boundary (based on a limited series of sine and cosine
functions) and information from the image intensity gradients along the
radii. The method is based on filtering by a modified Canny-Deriche
edge detector and then on minimization of an energy function based on
five parts. Since echoes from blood in the lumen and the thrombus
produce similar patterns and speckle noise, a modified version for
identifying the lumen-thrombus border was developed. The method has
been validated by various ways, including parameter sensitivity testing
and comparison to the performance of an expert. It is robust enough to
track the lumen and total arterial cross-sectional area changes during
the cardiac cycle. In 34 patients where sequences of images were
acquired, the border between the thrombus and the arterial wall was
detected with errors less than 2%, while the lumen-thrombus border was
detected with a mean error of 4%. Thus, a noninvasive measurement of
the AAA cross-sectional area is presented, which has been validated and
found to be accurate.
|
632. | Gatzoulis, L, Watson, RJ, Jordan, LB, Pye, SD, Anderson, T, Uren, N, Salter, DM, Fox, KAA, and McDicken, WN, "Three-dimensional forward-viewing intravascular ultrasound imaging of human arteries in vitro," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 27, pp. 969-982, 2001.
Abstract:
The aim of this work was to investigate the suitability of a novel
forward-viewing intravascular ultrasound (IVUS) technique for
three-dimensional imaging of severely stenosed or totally occluded
vessels, where the conventional side-viewing IVUS systems are of
limited use. A stiff 3.8 mm diameter forward-viewing catheter was
manufactured to scan a 72 degrees sector ahead of its tip. Conical
volume data were acquired by rotating the catheter over 180 degrees by
means of a motorised mechanical system. Operating at 30 MHz, the
catheter was integrated with an IVUS scanner and a radiofrequency data
acquisition system. Postmortem carotid and femoral arteries were
scanned in vitro. Correlation of the reconstructed images with
histology demonstrated the ability of this forward-viewing IVUS system
to visualise healthy lumens, bifurcations, thickened atherosclerotic
walls and, most importantly, severe and complete vessel occlusions. A
rotating-sector forward-viewing IVUS system is suitable for anatomical
assessment of severely diseased vessels in three dimensions.
|
633. | Kerschner, M, "Seamline detection in colour orthoimage mosaicking by use of twin snakes," ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, vol. 56, pp. 53-64, 2001.
Abstract:
In the last step of the mosaic production chain. neighbouring and
partly overlapping orthoimages of a scene are merged to one mosaic.
This should be done in a way that the transition from one to another
orthoimage cannot be seen. The production line of orthoimages consists
of several steps, each of which can introduce a different appearance
regarding geometry, radiometry and spectral properties to the resulting
orthoimage. For mosaicking adjacent orthoimages. a path of lowest
difference in a combination of criteria is searched in the overlap area
of these images. The seamline is chosen along this path of maximum
similarity. In this paper, criteria for such an optimal seamline in
colour orthoimages are elaborated. The main requirements are on one
hand high colour similarity of the images (mainly in hue and
intensity), and on the other hand high texture similarity (in
orientation and magnitude of image gradients). The specified criteria
are formulated in the energy function of snakes. A snake is an active
contour which moves through an image and changes its shape until a
minimum of its energy function is found. We use two snakes that attract
one another (twin snakes). In a hierarchical strategy, a proper
seamline is delineated fully automatically. The potential of the method
is shown with an example. (C) 2001 Elsevier Science B.V. Alt rights
reserved.
|
634. | Chen, JX, Wechsler, H, Pullen, JM, Zhu, Y, and MacMahon, EB, "Knee surgery assistance: Patient model construction, motion simulation, and biomechanical visualization," IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, vol. 48, pp. 1042-1052, 2001.
Abstract:
We present a new system that integrates computer graphics,
physics-based modeling, and interactive visualization to assist knee
study and surgical operation. First, we discuss generating
patient-specific three-dimensional (3-D) knee models from patient's
magnetic resonant images (MRIs). The 3-D model is obtained by deforming
a reference model to match the MRI dataset. Second, we present
simulating knee motion that visualizes patient-specific motion data on
the patient-specific knee model. Third, we introduce visualizing
biomechanical information on a patient-specific model. The focus is on
visualizing contact area, contact forces, and menisci deformation.
Traditional methods have difficulty in visualizing knee contact area
without using invasive methods. The approach presented here provides an
alternative of visualizing the knee contact area and forces without any
risk to the patient. Finally, a virtual surgery can be performed. The
constructed 3-D knee model is the basis of motion simulation,
biomechanical visualization, and virtual surgery. Knee motion
simulation determines the knee rotation angles as well as knee contact
points. These parameters are used to solve the biomechanical model. Our
results integrate 3-D construction, motion simulation, and
biomechanical visualization into one system. Overall, the methodologies
here are useful elements for future virtual medical systems where all
the components of visualization, automated model generation, and
surgery simulation come together.
|
635. | Eriksson, M, and Papanikolopoulos, NP, "Driver fatigue: a vision-based approach to automatic diagnosis," TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, vol. 9, pp. 399-413, 2001.
Abstract:
In this paper, we describe a system that locates and tracks the eyes of
a driver. The purpose of such a system is to perform detection of
driver fatigue. By mounting a small camera inside the car, we can
monitor the face of the driver and look for eye movements which
indicate that the driver is no longer in condition to drive. In such a
case, a warning signal should be issued. This paper describes how to
find and track the eyes. We also describe a method that can determine
if the eyes are open or closed. The primary criterion for this system
is that it must be highly non-intrusive. The system must also operate
regardless of the texture and the color of the face. It must also be
able to handle changing conditions such as changes in light, shadows,
reflections, etc. Initial experimental results are very promising even
when the driver moves his/her head in a way such that the camera does
not have a frontal view of the driver's face. (C) 2001 Elsevier Science
Ltd. All rights reserved.
|
636. | Kosmopoulos, D, and Varvarigou, T, "Automated inspection of gaps on the automobile production line through stereo vision and specular reflection," COMPUTERS IN INDUSTRY, vol. 46, pp. 49-63, 2001.
Abstract:
One of the most difficult tasks in the later stages of automobile
assembly is the dimensional inspection of the gaps between the car body
and the various panels fitted on it (doors, motor-hood, etc.). The
employment of an automatic gap-measuring system would reduce the costs
significantly and would offer high flexibility. However, this task is
still performed by humans and only a few - still experimental -
automatic systems have been reported. In this paper, we introduce a
system for automated gap inspection that employs computer vision. It is
capable of measuring the lateral and the range dimension of the gap
(width and flush, correspondingly). The measurement installation
consists of two calibrated stereo cameras and two infrared LED lamps,
used for highlighting the edges of the gap through specular reflection.
The gap is measured as the 3D distance between the highlighted edges.
This method has significant advantages against the laser-based,
gap-measuring systems, mainly due to its color independency. Our
approach has been analytically described in 2D and extensively
evaluated using synthetic as well as real gaps. The results obtained
verify its robustness and its applicability in an industrial
environment. (C) 2001 Published by Elsevier Science B.V.
|
637. | Delingette, H, and Montagnat, J, "Shape and topology constraints on parametric active contours," COMPUTER VISION AND IMAGE UNDERSTANDING, vol. 83, pp. 140-171, 2001.
Abstract:
In recent years, the field of active contour-based image segmentation
has seen the emergence of two competing approaches. The first and
oldest approach represents active contours in an explicit (or
parametric) manner corresponding to the Lagrangian formulation. The
second approach represents active contours in an implicit manner
corresponding to the Eulerian framework. After comparing these two
approaches, we describe several new topological and physical
constraints applied to parametric active contours in order to combine
the advantages of these two contour representations. More precisely, we
introduce three algorithms related to the control of the contour
topology, geometry, and deformation. The first algorithm controls both
vertex spacing and contour smoothness in an independent and intrinsic
manner. The second algorithm controls the contour resolution (number of
vertices) while the third algorithm automatically creates or fuses
connected components on closed or opened contours. The efficiency of
these algorithms is demonstrated on several images including medical
images and a comparison with the level-sets method is also provided.
(C) 2001 Academic Press.
|
638. | Lorigo, LM, Faugeras, OD, Grimson, WEL, Keriven, R, Kikinis, R, Nabavi, A, and Westin, CF, "CURVES: Curve evolution for vessel segmentation," MEDICAL IMAGE ANALYSIS, vol. 5, pp. 195-206, 2001.
Abstract:
The vasculature is of utmost importance in neurosurgery. Direct
visualization of images acquired with current imaging modalities,
however, cannot provide a spatial representation of small vessels.
These vessels, and their branches which show considerable variations,
are most important in planning and performing neurosurgical procedures.
In planning they provide information on where the lesion draws its
blood supply and where it drains. During surgery the vessels serve as
landmarks and guidelines to the lesion. The more minute the information
is, the more precise the navigation and localization of computer guided
procedures. Beyond neurosurgery and neurological study, vascular
information is also crucial in cardiovascular surgery, diagnosis, and
research. This paper addresses the problem of automatic segmentation of
complicated curvilinear structures in three-dimensional imagery, with
the primary application of segmenting vasculature in magnetic resonance
angiography (MRA) images. The method presented is based on recent curve
and surface evolution work in the computer vision community which
models the object boundary as a manifold that evolves iteratively to
minimize an energy criterion. This energy criterion is based both on
intensity values in the image and on local smoothness properties of the
object boundary, which is the vessel wall in this application. In
particular, the method handles curves evolving in 3D, in contrast with
previous work that has dealt with curves in 2D and surfaces in 3D.
Results are presented on cerebral and aortic MRA data as well as lung
computed tomography (CT) data. (C) 2001 Elsevier Science B.V. All
rights reserved.
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639. | Goldenberg, R, Kimmel, R, Rivlin, E, and Rudzsky, M, "Fast geodesic active contours," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 1467-1475, 2001.
Abstract:
We use an unconditionally stable numerical scheme to implement a fast
version of the geodesic active contour model. The proposed scheme is
useful for object segmentation in images, like tracking moving objects
in a sequence of images. The method is based on the
Weickert-Romeney-Viergever (additive operator splitting) AOS scheme. It
is applied at small regions, motivated by Adalsteinsson-Sethian level
set narrow band approach, and uses Sethian's fast marching method for
re-initialization. Experimental results demonstrate the power of the
new method for tracking in color movies.
|
640. | Fernandez-Caballero, A, Mira, J, Fernandez, MA, and Lopez, MT, "Segmentation from motion of non-rigid objects by neuronal lateral interaction," PATTERN RECOGNITION LETTERS, vol. 22, pp. 1517-1524, 2001.
Abstract:
The problem we are stating is the discrimination of non-rigid objects
capable of holding our attention in a scene. Motion allows gradually
obtaining all moving objects shapes. We introduce an algorithm that
fuses spots obtained by means of neuronal lateral interaction in
accumulative computation. (C) 2001 Elsevier Science B.V. All rights
reserved.
|
641. | Pardas, M, and Sayrol, E, "Motion estimation based tracking of active contours," PATTERN RECOGNITION LETTERS, vol. 22, pp. 1447-1456, 2001.
Abstract:
This paper addresses the application of active contours or snakes for
tracking of contours in image sequences. We propose to use the dynamic
programming implementation of the snakes in order to restrict the
possible candidates for a given snaxel to those that have a high
correlation with the corresponding snaxel in the previous frame.
Besides, we claim that, in tracking applications, the motion
compensation error has to be introduced in the external energy of the
snake to be able to track generic contours. (C) 2001 Elsevier Science
B.V. All rights reserved.
|
642. | Ferrant, M, Macq, B, Nabavi, A, and Warfield, SK, "Deformable modeling for characterizing biomedical shape changes," DISCRETE GEOMETRY FOR COMPUTER IMAGERY, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1953, pp. 235-248, 2001.
Abstract:
We present a new algorithm for modeling and characterizing shape
changes in 3D image sequences of biomedical structures. Our algorithm
tracks the shape changes of the objects depicted in the image sequence
using an active surface algorithm. To characterize the deformations of
the surrounding and inner volume of the object's surfaces, we use a
physics-based model of the objects the image represents. In the
applications we are presenting, our physics-based model is linear
elasticity and we solve the corresponding equilibrium equations using
the Finite Element (FE) method. To generate a FE mesh from the initial
3D image, we have developed a new multiresolution tetrahedral mesh
generation algorithm specifically suited for labeled image volumes. The
shape changes of the surfaces of the objects are used as boundary
conditions to our physics-based FE model and allow us to infer a
volumetric deformation field from the surface deformations.
Physics-based measures such as stress tensor maps can then be derived
from our model for characterizing the shape changes of the objects in
the image sequence. Experiments on synthetic images as well as on
medical data show the performances of the algorithm.
|
643. | Koozekanani, D, Boyer, K, and Roberts, C, "Retinal thickness measurements from optical coherence tomography using a Markov boundary model," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 900-916, 2001.
Abstract:
We present a system for detecting retinal boundaries in optical
coherence tomography (OCT) B-scans. OCT is a relatively new imaging
modality giving cross-sectional images that are qualitatively similar
to ultrasound. However, the axial resolution with OCT is much higher.
on the order of 10 mum. Objective, quantitative measures of retinal
thickness may be made from OCT images. Knowledge of retinal thickness
is important in the evaluation and treatment of many ocular diseases.
The boundary-detection system presented here uses a one-dimensional
edge-detection kernel to yield edge primitives. These edge primitives
are rated, selected, and organized to form a coherent boundary
structure by use of a Markov model of retinal boundaries as detected by
OCT. Qualitatively, the boundaries detected by the automated system
generally agreed extremely well with the true retinal structure for the
vast majority of OCT images. Only one of the 1450 evaluation images
caused the algorithm to fail. A quantitative evaluation of the retinal
boundaries was performed as well, using the clinical application of
automatic retinal thickness determination. Retinal thickness
measurements derived from the algorithm's results were compared with
thickness measurements from manually corrected boundaries for 1450 test
images. The algorithm's thickness measurements over a 1-mm region near
the fovea differed from the corrected thickness measurements by less
than 10 mum for 74% of the images and by less than 25 mum (10% of
normal retinal thickness) for 98.4% of the images. These errors are
near the machine's resolution limit and still well below clinical
significance. Current, standard clinical practice involves a
qualitative, visual assessment of retinal thickness. A robust,
quantitatively accurate system such as ours can be expected to improve
patient care.
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644. | Torheim, G, Amundsen, T, Rinck, PA, Haraldseth, O, and Sebastiani, G, "Analysis of contrast-enhanced dynamic MR images of the lung," JOURNAL OF MAGNETIC RESONANCE IMAGING, vol. 13, pp. 577-587, 2001.
Abstract:
Recent studies have demonstrated the potential of dynamic
contrast-enhanced magnetic resonance Imaging (MRI) describing pulmonary
perfusion. However, breathing motion, susceptibility artifacts, and a
low signal-to-noise ratio (SNR) make automatic pixel-by-pixel analysis
difficult. In the present work, we propose a novel method to compensate
for breathing motion. In order to test the feasibility of this method,
we enrolled 53 patients with pulmonary embolism (N = 24), chronic
obstructive pulmonary disease (COPD) (N = 14), and acute pneumonia (N =
15). A crucial part of the method, an automatic diaphragm detection
algorithm, was evaluated in all 53 patients by two Independent
observers. The accuracy of the method to detect the diaphragm showed a
success rate of 92%. Furthermore, a Bayesian noise reduction technique
was implemented and tested. This technique significantly reduced the
noise level without removing important clinical information. In
conclusion, the combination of a motion correction method and a
Bayesian noise reduction method offered a rapid, semiautomatic
pixel-by-pixel analysis of the lungs with great potential for research
and clinical use. (C) 2001 Wiley-Liss, Inc.
|
645. | Qatarneh, SM, Crafoord, J, Kramer, EL, Maguire, GQ, Brahme, A, Noz, ME, and Hyodynmaa, S, "A whole body atlas for segmentation and delineation of organs for radiation therapy planning," NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, vol. 471, pp. 160-164, 2001.
Abstract:
A semi-automatic procedure for delineation of organs, to be used as the
basis of a whole body atlas database for radiation therapy planning was
developed. The Visible Human Male Computed Tomography (CT)-data set was
used as a "standard man" reference. The organ of interest was outlined
manually and then transformed by a polynomial warping algorithm onto a
clinical patient CT. This provided an initial contour, which was then
adjusted and refined by the semi-automatic active contour model to find
the final organ outline. The liver was used as a test organ for
evaluating the performance of the procedure. Liver outlines obtained by
the segmentation algorithm on six patients were compared to those
manually drawn by, a radiologist. The combination of warping and
semi-automatic active contour model generally provided satisfactory
segmentation results, but the procedure has to be extended to three
dimensions. (C) 2001 Elsevier Science B.V. All rights reserved.
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646. | Biscay, RJ, and Mora, CM, "Metric sample spaces of continuous geometric curves and estimation of their centroids," MATHEMATISCHE NACHRICHTEN, vol. 229, pp. 15-49, 2001.
Abstract:
The metric sample space of Frechet curves (FRECHET, 1934, 1951, 1961)
is based on a generalization of regular curves that covers continuous
curves in full generality. This makes it possible to deal with both
smooth and non-smooth, even non-rectifiable geometric curves in
statistical analysis. In the present paper this sample space is further
extended in two directions that are relevant in practice: to
incorporate information on landmark points in the curves and to impose
invariance with respect to an arbitrary group of isometric spatial
transformations. Properties of the introduced sample spaces of curves
are studied, specially those concerning to the generation and
representation of random curves by random functions. In order to
provide measures of central tendency and dispersion of random curves,
centroids and restricted centroids of random curves are defined in a
general metric framework, and methods for their consistent estimation
are derived.
|
647. | Aissaoui, R, Kauffmann, C, Dansereau, J, and de Guise, JA, "Analysis of pressure distribution at the body-seat interface in able-bodied and paraplegic subjects using a deformable active contour algorithm," MEDICAL ENGINEERING & PHYSICS, vol. 23, pp. 359-367, 2001.
Abstract:
In this paper, a semi-automatic method for segmenting pressure
distribution image-based data at the body-seat interface is presented.
The purpose of this work was to estimate the surface and the load
supported by the ischial tuberosity (IT) region. The proposed method
involves three steps: (1) detecting the IT region using a
pressure-distribution image gradient; (2) estimating the contour of the
IT region by an iterative active contour algorithm and finally (3)
estimating the percentage of the surface and the weight-bearing of the
IT region in a group of able-bodied (AB) and spinal-cord injury (SCI)
subjects. It was found in this study that the weight bearing on the IT
for the spinal-cord injured group is distributed on half the surface in
comparison with the AB group or the powered wheelchair users groups.
The findings of this study provide insights concerning pressure
distribution in sitting for the paraplegic and able-bodied. (C) 2001
IPEM. Published by Elsevier Science Ltd. All rights reserved.
|
648. | Jermyn, IH, and Ishikawa, H, "Globally optimal regions and boundaries as minimum ratio weight cycles," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 23, pp. 1075-1088, 2001.
Abstract:
We describe anew form of energy functional for the modeling and
identification of regions in images. The energy is defined on the space
of boundaries in the image domain and can incorporate very general
combinations of modeling information both from the boundary (intensity
gradients, etc.) and from the interior of the region (texture,
homogeneity, etc.). We describe two polynomial-time digraph algorithms
for finding the global minima of this energy. One of the algorithms is
completely general, minimizing the functional for any choice of
modeling information. It runs in a few seconds on a 256x256 image. The
other algorithm applies to a subclass of functionals, but has the
advantage of being extremely parallelizable. Neither algorithm requires
initialization.
|
649. | Yan, H, "Fuzzy curve-tracing algorithm," IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, vol. 31, pp. 768-780, 2001.
Abstract:
This paper presents a fuzzy clustering algorithm for the extraction of
a smooth curve from unordered noisy data. In this method, the input
data are first clustered into different regions using the fuzzy c-means
algorithm and each region is represented by its cluster center.
Neighboring cluster centers are linked to produce a graph according to
the average class membership values. Loops in the graph are removed to
form a curve according to spatial relations of the cluster centers. The
input samples are then reclustered using the fuzzy c-means (FCM)
algorithm, with the constraint that the curve must be smooth. The
method has been tested with both open and closed curves with good
results.
|
650. | Nikou, C, Bueno, G, Heitz, F, and Armspach, JP, "A joint physics-based statistical deformable model for multimodal brain image analysis," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 1026-1037, 2001.
Abstract:
A probabilistic deformable, model for the representation of multiple
brain structures is described. The statistically learned deformable
model! represents the relative location of different anatomical
surfaces in brain magnetic resonance images (MRIs) and accommodates
their significant variability across different individuals. The
surfaces of each anatomical structure are parameterized by the
amplitudes of the vibration modes of a deformable spherical mesh. For a
given MRI in the training set, a vector containing the largest
vibration modes describing the different deformable surfaces is
created. This random vector is statistically constrained by retaining
the most significant variation modes of its Karhunen-Loeve expansion on
the training population. By these means, the conjunction of surfaces
are deformed according to the anatomical variability observed in the
training set. Two applications of the joint probabilistic deformable
model are presented: isolation of the brain from MRI using the
probabilistic constraints embedded in the model; and deformable
model-based registration of three-dimensional multimodal (magnetic
resonance/single photon emission computed tomography) brain images
without removing nonbrain structures. The multiobject deformable model
may be considered as a first step toward the development of a general
purpose probabilistic anatomical atlas of the brain.
|
651. | Vincze, M, "Robust tracking of ellipses at frame rate," PATTERN RECOGNITION, vol. 34, pp. 487-498, 2001.
Abstract:
The critical issue in vision-based control of motion is robust tracking
at real time. A method is presented that tracks ellipses at field rate
using a Pentium PC. Robustness is obtained by integrating gradient
information and mode (intensity) values for the detection of edgels
along the contour of the ellipse and by using a probabilistic
(RANSAC-like, Fischler and Bolles, Commun. ACM 24(6) (1981) 381) method
to find the most likely ellipse-shaped object. Detailed experiments
document the capabilities and limitations of the approach and the
robustness achieved. (C) 2000 Pattern Recognition Society. Published by
Elsevier Science Ltd. All rights reserved.
|
652. | Son, JD, and Ko, HS, "Robust motion tracking of multiple objects with KL-IMMPDAF," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E84D, pp. 179-187, 2001.
Abstract:
This paper describes how the image sequences taken by a stationary
video camera may be effectively processed to detect and track moving
objects against a stationary background in real-time. Our approach is
first to isolate the moving objects in image sequences via a modified
adaptive background estimation method and then perform token tracking
of multiple objects based oil features extracted from the processed
image sequences. In feature based multiple object tracking, the most
prominent, tracking issues are track initialization, data association,
occlusions tills to traffic congestion, and object maneuvering. While
there are limited past works addressing these problems, most relevant
tracking systems proposed in the past are independently focused to
either "occlusion" or "data association" only. In this paper, we
propose the KL-IMMPDA (Kanade Lucas-Interacting Multiple Model
Probabilistic Data Association) filtering approach for multiple-object
tracking to collectively address the key issues. The proposed method
essentially employs optical flow measurements for both detection and
track initialization while the KL-IMMPDA filter is used to accept or
reject measurements, which belong to other objects. The data
association performed by the proposed KL-IMMPDA results in an effective
tracking scheme, which is robust to partial occlusions and image
clutter of object maneuvering. The simulation results show a
significant performance improvement for tracking multi-objects in
occlusion and maneuvering, when compared to other conventional trackers
such as Kalman filter.
|
653. | Luo, YH, and Nelson, BJ, "Fusing force and vision feedback for manipulating deformable objects," JOURNAL OF ROBOTIC SYSTEMS, vol. 18, pp. 103-117, 2001.
Abstract:
This article describes a framework that fuses vision and force feedback
for the control of highly deformable objects. Deformable active
contours, or snakes, are used to visually observe changes in object
shape over time. Finite-element models of object deformations are used
with force feedback to predict expected visually observed deformations.
Our approach improves the performance of large, complex deformable
contour tracking over traditional computer vision tracking techniques.
This same approach of combining deformable active contours with
finite-element material models is modified so that a vision sensor,
i.e., a charge-coupled device (CCD) camera, can be used as a force
sensor. By visually tracking changes in contours on the object,
material deflections can be transformed into applied stress estimates
through finite element modeling. Therefore, internal object stresses
due to object manipulation can be visually observed and controlled,
thus creating a framework for deformable object manipulation. A pinhole
camera model is used to accomplish vision and force sensor feedback
assimilation from these two sensing modalities during manipulation, (C)
2001 John Wiley & Sons, Inc.
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654. | Manh, AG, Rabatel, G, Assemat, L, and Aldon, MJ, "Weed leaf image segmentation by deformable templates," JOURNAL OF AGRICULTURAL ENGINEERING RESEARCH, vol. 80, pp. 139-146, 2001.
Abstract:
In order to improve weeding strategies in terms of pesticide reduction,
spatial distribution and characterization of in-field weed populations
are important. With recent improvements in image processing, many
studies have focused on weed detection by vision techniques. However,
weed identification still remains difficult because of outdoor scenic
complexity and morphological variability of plants.
A new method of weed leaf segmentation based on the use of deformable
templates is proposed. This approach has the advantage of applying a
priori knowledge to the object searched, improving the robustness of
the segmentation stage. The principle consists of fitting a parametric
model to the leaf outlines in the image, by minimizing an energy term
related to internal constraints of the model and salient features of
the image, such as the colour of the plant.
This method showed promising results for one weed species, green
foxtail (Setaria viridis). In particular, it was possible to
characterize partially occluded leaves. This constitutes a first step
towards a recognition system, based on leaf characteristics and their
relative spatial position. (C) 2001 Silsoe Research Institute.
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655. | Fukuda, T, Morimoto, Y, Morishita, S, and Tokuyama, T, "Data mining with optimized two-dimensional association rules," ACM TRANSACTIONS ON DATABASE SYSTEMS, vol. 26, pp. 179-213, 2001.
Abstract:
We discuss data mining based on association rules for two numeric
attributes and one Boolean attribute. For example, in a database of
bank customers, "Age" and "Balance" are two numeric attributes, and
"CardLoan" is a Boolean attribute. Taking the pair (Age, Balance) as a
point in two-dimensional space, we consider an association rule of the
form
((Age, Balance) is an element of P) double right arrow (CardLoan = Yes),
which implies that bank customers whose ages and balances fall within a
planar region P tend to take out credit card loans with a high
probability. We consider two classes of regions, rectangles and
admissible (i.e., connected and x-monotone) regions. For each class, we
propose efficient algorithms for computing the regions that give
optimal association rules for gain, support, and confidence,
respectively. We have implemented the algorithms for admissible regions
as well as several advanced functions based on them in our data mining
system named SONAR (System for Optimized Numeric Association Rules),
where the rules are visualized by using a graphic user interface to
make it easy for users to gain an intuitive understanding of rules.
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656. | Kaygin, S, and Bulut, MM, "A new one-pass algorithm to detect region boundaries," PATTERN RECOGNITION LETTERS, vol. 22, pp. 1169-1178, 2001.
Abstract:
In this paper, active chain is introduced as a chain coded contour
whose shape is changed during iterations while it stays closed,
clockwise and 4 connected. The iterations of the proposed algorithm
move the chain items toward the interior region. This behaviour is
similar to the active contours (snakes). If the initial contour is
counter-clockwise, the same algorithm causes the active chain to expand
like a balloon and detect the inner boundaries of the regions. The
chain coded contours of all the separate regions can be detected in one
pass in O(NM) where N and M are the image dimensions in pixels. (C)
2001 Elsevier Science B.V. All rights reserved.
|
657. | Tsai, A, Yezzi, A, and Willsky, AS, "Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 1169-1186, 2001.
Abstract:
In this work, we first address the problem of simultaneous image
segmentation and smoothing by approaching the Mumford-Shah paradigm
from a curve evolution perspective. In particular, we let a set of
deformable contours define the boundaries between regions in an image
where we model the data via piecewise smooth functions and employ a
gradient flow to evolve these contours. Each gradient step involves
solving an optimal estimation problem for the data within each region,
connecting curve evolution and the Mumford-Shah functional with the
theory of boundary-value stochastic processes. The resulting active
contour model offers a tractable implementation of the original
Mumford-Shah model (i.e., without resorting to elliptic approximations
which have traditionally been favored for greater ease in
implementation) to simultaneously segment and smoothly reconstruct the
data within a given image in a coupled manner. Various implementations
of this algorithm are introduced to increase its speed of convergence.
We also outline a hierarchical implementation of this algorithm to
handle important image features such as triple points and other
multiple junctions. Next, by generalizing the data fidelity term of the
original Mumford-Shah functional to incorporate a spatially varying
penalty, we extend our method to problems in which data quality varies
across the image and to images in which sets of pixel measurements are
missing. This more general model leads us to a novel PDE-based approach
for simultaneous image magnification, segmentation, and smoothing,
thereby extending the traditional applications of the Mumford-Shah
functional which only considers simultaneous segmentation and smoothing.
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658. | Hsu, CC, Lai, PH, Lee, C, and Huang, WC, "Automated nasopharyngeal carcinoma detection with dynamic gadolinium-enhanced MR imaging," METHODS OF INFORMATION IN MEDICINE, vol. 40, pp. 331-337, 2001.
Abstract:
Objectives. The purpose of this research is to develop an automatic
medical diagnosis for segmenting nasopharyngeal carcinoma (NPC) with
dynamic gadolinium-enhanced MR imaging.
Methods: This system is a multistage process, involving motion
correction, head mask generation, dynamic MR data quantitative
evaluation, rough segmentation, and rough segmentation refinement. Two
approaches, a relative signal increase method and a slope method, are
proposed for the quantitative evaluation of dynamic MR data.
Results. The NPC detection results obtained using the proposed methods
had a rating of 85% in match percent compared with these lesions
identified by an experienced radiologist. The match percent for the two
proposed methods did not have significant differences. However, the
computation cost for the slope method was about twelve times faster
than the relative signal increase method.
Conclusions. The proposed methods can identify the NPC regions quickly
and effectively. This system can enhance the performance of clinical
diagnosis.
|
659. | Pitermann, M, and Munhall, KG, "An inverse dynamics approach to face animation," JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, vol. 110, pp. 1570-1580, 2001.
Abstract:
Muscle-based models of the human face produce high quality animation
but rely on recorded muscle activity signals or synthetic muscle
signals that are often derived by trial and error. This paper presents
a dynamic inversion of a muscle-based model (Lucero and Munhall, 1999)
that permits the animation to be created from kinematic recordings of
facial movements. Using a nonlinear optimizer (Powell's algorithm), the
inversion produces a muscle activity set for seven muscles in the lower
face that minimize the root mean square error between kinematic data
recorded with OPTOTRAK and the corresponding nodes of the modeled
facial mesh. This inverted muscle activity is then used to animate the
facial model. In three tests of the inversion, strong correlations were
observed for kinematics produced from synthetic muscle activity, for
OPTOTRAK kinematics recorded from a talker for whom the facial model is
morphologically adapted and finally for another talker with the model
morphology adapted to a different individual. The correspondence
between the animation kinematics and the three-dimensional OPTOTRAK
data are very good and the animation is of high quality. Because the
kinematic to electromyography (EMG) inversion is ill posed, there is no
relation between the actual EMG and the inverted EMG. The overall
redundancy of the motor system means that many different EMG patterns
can produce the same kinematic output. (C) 2001 Acoustical Society of
America.
|
660. | Ohtake, Y, and Belyaev, AG, "Mesh optimization for polygonized isosurfaces," COMPUTER GRAPHICS FORUM, vol. 20, pp. C368-C376, 2001.
Abstract:
In this paper we propose a method for improvement of isosurface
polygonizations. Given an initial polygonization of an isosurface, we
introduce a mesh evolution process initialized by the polygonization.
The evolving mesh converges quickly to its limit mesh which provides
with a high quality approximation of the isosurface even if the
isosurface has sharp features, boundary, complex topology. To analyze
how close the evolving mesh approaches its destined isosurface, we
introduce error estimators measuring the deviations of the mesh
vertices from the isosurface and mesh normals from the isosurface
normals. A new technique for mesh editing with isosurfaces is also
proposed. In particular it can be used for creating carving effects.
|
661. | Latson, LA, Powell, KA, Sturm, B, Schvartzman, PR, and White, RD, "Clinical validation of an automated boundary tracking algorithm on cardiac MR images," INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING, vol. 17, pp. 279-286, 2001.
Abstract:
The goal of this research was to develop an automated algorithm for
tracking the borders of the left ventricle (LV) in a cine-MRI
gradient-echo temporal data set. The algorithm was validated on four
patient populations: healthy volunteers and patients with dilated
cardiomyopathy (DCM), left ventricular hypertrophy (LVH), or left
ventricular aneurysm (LVA). A full tomographic set (similar to 11
slices/case) of short-axis images through systole was obtained for each
patient. Initial endocardial and epicardial contours for the
end-diastolic (ED) and end-systolic (ES) frames were manually traced on
the computer by an experienced radiologist. The ED tracings were used
as the starting point for the algorithm. The borders were tracked
through each phase of the temporal data set, until the ES frame was
reached (similar to7 phases/slice). Peak gradients along equally spaced
chords calculated perpendicular to a centerline determined midway
between the endocardial and epicardial borders were used for border
detection. This approach was tested by comparing the LV epicardial and
endocardial volumes calculated at ES to those based on the manual
tracings. The results of the algorithm compared favorably with both the
endocardial (r(2) = 0.72 - 0.98) and epicardial (r(2) = 0.96 - 0.99)
volumes of the tracer.
|
662. | Schmidt-Trucksass, A, Cheng, DC, Sandrock, M, Schulte-Monting, J, Rauramaa, R, Huonker, M, and Burkhardt, H, "Computerized analysing system using the active contour in ultrasound measurement of carotid artery intima-media thickness," CLINICAL PHYSIOLOGY, vol. 21, pp. 561-569, 2001.
Abstract:
Background and purpose B-mode measurement of the carotid intima-media
(IM) thickness (T) based on manual tracing (MT) procedures are
dependent on the subjectivity of the reader and the existing automatic
tracing procedures often fail to detect the IM boundaries accurately.
The purpose of this study was to compare the tracing results of the IM
boundaries of the carotid wall with a new automatic identification (AI)
procedure, based on an active contour model, and computer-assisted
manual tracing (MT).
Methods The detection of the IM boundaries was performed with both
procedures in 126 ultrasound images [63 each of the common carotid
artery (CCA) and carotid bulb] along the far wall of the distal CCA and
the carotid bulb. Intra- and inter-reader variability for mean and
maximum IMT with AI and MT and accuracy of identification of both IM
boundaries were evaluated.
Results Using MT the intra- and inter-reader variability amounted to
0.01-0.03 and 0.03-0.07 mm, respectively. The variability was slightly
higher in the carotid bulb than in the CCA. Using AI the variability
was almost eliminated. Mean and maximum IMT were measured
systematically lower by AI compared with MT in all regions by 0.01 mm.
The accuracy of identification was similar for both IM boundaries, but
lower in the carotid bulb region than in the CCA.
Conclusions The new AI procedure identifies both IM boundaries in the
region of the far wall of the CCA and carotid bulb with high precision,
and eliminates most of the intra- and inter-reader variability of the
IMT measurement using MT.
|
663. | Park, J, and Keller, JM, "Snakes on the watershed," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 23, pp. 1201-1205, 2001.
Abstract:
In this paper, we present a new approach for object boundary
extraction, called the watersnake. It is a two-step snake algorithm
whose energy functional is minimized by the dynamic programming method.
It is more robust to local minima because it finds the solution by
searching the entire energy space. To reduce the complexity of the
minimization process, the watershed transformation and a coarse-to-fine
strategy are used. The new technique is compared to standard methods
for accuracy in synthetic data and is applied to segmentation of white
blood cells in bone marrow Images.
|
664. | Moghaddam, B, Nastar, C, and Pentland, A, "A Bayesian similarity measure for deformable image matching," IMAGE AND VISION COMPUTING, vol. 19, pp. 235-244, 2001.
Abstract:
We propose a probabilistic similarity measure for direct image matching
based on a Bayesian analysis of image deformations. We model two
classes of variation in object appearance: intra-object and
extra-object. The probability density functions for each class are then
estimated from training data and used to compute a similarity measure
based on the a posteriori probabilities. Furthermore, we use a novel
representation for characterizing image differences using a deformable
technique for obtaining pixel-wise correspondences. This
representation, which is based on a deformable 3D mesh in XYI-space, is
then experimentally compared with two simpler representations:
intensity differences and optical Row. The performance advantage of our
deformable matching technique is demonstrated using a typically hard
test set drawn from the US Army's FERET face database. (C) 2001
Elsevier Science B.V. All rights reserved.
|
665. | Bhalerao, A, and Wilson, R, "Unsupervised image segmentation combining region and boundary," IMAGE AND VISION COMPUTING, vol. 19, pp. 353-368, 2001.
Abstract:
An integrated approach to image segmentation is presented that combines
region and boundary information using maximum a posteriori estimation
and decision theory. The algorithm employs iterative, decision-directed
estimation performed on a novel multi-resolution representation. The
use of a multi-resolution technique ensures both robustness in noise
and efficiency of computation, while the model-based estimation and
decision process is flexible and spatially local, thus avoiding
assumptions about global homogeneity or size and number of regions. A
comparative evaluation of the method against region-only and
boundary-only methods is presented and is shown to produce accurate
segmentations at quite low signal-to-noise ratios. (C) 2001 Elsevier
Science B.V. All rights reserved.
|
666. | Gulick, VC, Morris, RL, Ruzon, MA, and Roush, TL, "Autonomous image analyses during the 1999 Marsokhod rover field test," JOURNAL OF GEOPHYSICAL RESEARCH-PLANETS, vol. 106, pp. 7745-7763, 2001.
Abstract:
A Martian rover capable of analyzing images autonomously could traverse
greater path lengths and return data with greater scientific content. A
more intelligent rover could, for example, automatically select targets
of interest (e.g., rocks, layers), return spectral or high-resolution
image data of these targets at the same time, remove less interesting
or redundant parts of images before transmitting them, and provide
compact information or representations of its environment. Three
prototype algorithms, a horizon detector, a rock detector, and a layer
detector have been developed and tested during the 1999 Marsokhod rover
field test in Silver Lake, California. The results are encouraging and
demonstrate the potential savings in time as well as the potential
increase in the amount of relevant science data returned in each
command cycle.
|
667. | Boykov, Y, Veksler, O, and Zabih, R, "Fast approximate energy minimization via graph cuts," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 23, pp. 1222-1239, 2001.
Abstract:
Many tasks in computer vision involve assigning a label (such as
disparity) to every pixel. A common constraint is that the labels
should vary smoothly almost everywhere while preserving sharp
discontinuities that may exist, e.g., at object boundaries. These tasks
are naturally stated in terms of energy minimization. In this paper, we
consider a wide class of energies with various smoothness constraints.
Global minimization of these energy functions is NP-hard even in the
simplest discontinuity-preserving case. Therefore, our focus is on
efficient approximation algorithms. We present two algorithms based on
graph cuts that efficiently find a local minimum with respect to two
types of large moves, namely expansion moves and swap moves. These
moves can simultaneously change the labels of arbitrarily large sets of
pixels. In contrast, many standard algorithms (including simulated
annealing) use small moves where only one pixel changes its label at a
time. Our expansion algorithm finds a labeling within a known factor of
the global minimum, while our swap algorithm handles more general
energy functions. Both of these algorithms allow important cases of
discontinuity preserving energies. We experimentally demonstrate the
effectiveness of our approach for image restoration, stereo and motion.
On real data with ground truth, we achieve 98 percent accuracy.
|
668. | Vemuri, BC, Guo, YL, and Wang, ZZ, "Deformable pedal curves and surfaces: Hybrid geometric active models for shape recovery," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 44, pp. 137-155, 2001.
Abstract:
In this paper, we propose significant extensions to the "snake pedal"
model, a powerful geometric shape modeling scheme introduced in (Vemuri
and Guo, 1998). The extension allows the model to automatically cope
with topological changes and for the first time, introduces the concept
of a compact global shape into geometric active models. The ability to
characterize global shape of an object using very few parameters
facilitates shape learning and recognition. In this new modeling
scheme, object shapes are represented using a parameterized
function-called the generator-which accounts for the global shape of an
object and the pedal curve (surface) of this global shape with respect
to a geometric snake to represent any local detail. Traditionally,
pedal curves (surfaces) are defined as the loci of the feet of
perpendiculars to the tangents of the generator from a fixed point
called the pedal point. Local shape control is achieved by introducing
a set of pedal points-lying on a snake-for each point on the generator.
The model dubbed as a "snake pedal" allows for interactive manipulation
via forces applied to the snake. In this work, we replace the snake by
a geometric snake and derive all the necessary mathematics for evolving
the geometric snake when the snake pedal is assumed to evolve as a
function of its curvature. Automatic topological changes of the model
may be achieved by implementing the geometric snake in a level-set
framework. We demonstrate the applicability of this modeling scheme via
examples of shape recovery from a variety of 2D and 3D image data.
|
669. | Harari, D, Furst, M, Kiryati, N, Caspi, A, and Davidson, M, "A computer-based method for the assessment of body-image distortions in anorexia-nervosa patients," IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, vol. 5, pp. 311-319, 2001.
Abstract:
A computer-based method for the assessment of body-image distortions in
anorexia nervosa and other eating-disorder patients is presented in
this paper. At the core of the method is a realistic pictorial
simulation of lifelike weight changes, applied to a real source image
of the patient. The patients, using a graphical user interface, adjust
their body shapes until they meet their self-perceived appearance.
Measuring the extent of virtual fattening or slimming of a body with
respect to its real shape and size allows direct quantitative
evaluation of the cognitive distortion in body image. In a preliminary
experiment involving 33 anorexia-nervosa patients, 70% of the subjects
chose an image with simulated visual weight gain between 8%-16% as
their "real" body image, while only one of them recognized the original
body image. In a second experiment involving 30 healthy participants,
the quality of the weight modified images was evaluated by pairwise
selection trials. Over a weight change range from -16% to +28%, in
about 30% of the trials, artificially modified images were mistakenly
taken as "original" images, thus demonstrating the quality of the
artificial images. The method presented is currently in a clinical
validation phase, toward application in the research, diagnosis,
evaluation, and treatment of eating disorders.
|
670. | Zoroofi, RA, Nishii, T, Sato, Y, Sugano, N, Yoshikawa, H, and Tamura, S, "Segmentation of avascular necrosis of the femoral head using 3-D MR images," COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, vol. 25, pp. 511-521, 2001.
Abstract:
Avascular necrosis of the femoral head (ANFH) is a common clinical
disorder in the orthopedic field. Traditional approaches to study the
extent of ANFH rely primarily on manual segmentation of clinical
magnetic resonance images (MRI). However, manual segmentation is
insufficient for quantitative evaluation and staging of ANFH. This
paper presents a new computerized approach for segmentation of necrotic
lesions of the femoral head. The segmentation method consists of
several steps including histogram based thresholding, 3-D morphological
operations, oblique data reconstruction, and 2-D ellipse fitting. The
proposed technique is rapid and efficient. In addition, it is available
as a Microsoft Windows free software package on the Internet.
Feasibility of the method is demonstrated on the data sets of 30
patients (1500 MR images). (C) 2001 Elsevier Science Ltd. All rights
reserved.
|
671. | Dumitras, A, and Venetsanopoulos, AN, "Angular map-driven snakes with application to object shape description in color images," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 1851-1859, 2001.
Abstract:
We propose a method for shape description of objects in color images.
Our method employs angular maps in order to identify significant
changes of color within the image, which are then used to drive snake
models. To obtain an angular map, the angle values of the vectors
corresponding to color image pixels are first computed with respect to
a reference vector, and organized in a two-dimensional matrix. To
identify significant color changes within the original image, the edges
of the angular map are next extracted. The resulting edge map is then
presented to a snake model. Distance and gradient vector flow snake
models have been employed in this work. Experimental results show, not
only that the resulting object shape descriptions are accurate and
quite similar, but also that our method is computationally efficient
and flexible.
|
672. | Barbosa, J, Tavares, J, and Padilha, AJ, "Parallel image processing system on a cluster of personal computers - Best student paper award: First prize," VECTOR AND PARALLEL PROCESSING - VECPAR 2000, LECTURE NOTES IN COMPUTER SCIENCE, vol. 1981, pp. 439-452, 2001.
Abstract:
The most demanding image processing applications require real time
processing, often using special purpose hardware. The work herein
presented refers to the application of cluster computing for off line
image processing, where the end user benefits from the operation of
otherwise idle processors in the local LAN. The virtual parallel
computer is composed by off-the-shelf personal computers connected by a
low cost network, such as a 10 Mbits/s Ethernet. The aim is to minimise
the processing time of a high level image processing package. The
system developed to manage the parallel execution is described and some
results obtained for the parallelisation of high level image processing
algorithms are discussed, namely for active contour and modal analysis
methods which require the computation of the eigenvectors of a
symmetric matrix.
|
673. | Berthilsson, R, Astrom, K, and Heyden, A, "Reconstruction of general curves, using factorization and bundle adjustment," INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 41, pp. 171-182, 2001.
Abstract:
In this paper, we extend the notion of affine shape, introduced by
Sparr, from finite point sets to curves. The extension makes it
possible to reconstruct 3D-curves up to projective transformations,
from a number of their 2D-projections. We also extend the bundle
adjustment technique from point features to curves.
The first step of the curve reconstruction algorithm is based on affine
shape. It is independent of choice of coordinates, is robust, does not
rely on any preselected parameters and works for an arbitrary number of
images. In particular this means that, except for a small set of curves
(e.g. a moving line), a solution is given to the aperture problem of
finding point correspondences between curves. The second step takes
advantage of any knowledge of measurement errors in the images. This is
possible by extending the bundle adjustment technique to curves.
Finally, experiments are performed on both synthetic and real data to
show the performance and applicability of the algorithm.
|
674. | Sahiner, B, Petrick, N, Chan, HP, Hadjiiski, LM, Paramagul, C, Helvie, MA, and Gurcan, MN, "Computer-aided characterization of mammographic masses: Accuracy of mass segmentation and its effects on characterization," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 1275-1284, 2001.
Abstract:
Mass segmentation is used as the first step in many computer-aided
diagnosis (CAD) systems for classification of breast masses as
malignant or benign. The goal of this paper was to study the accuracy
of an automated mass segmentation method developed in our laboratory,
and to investigate the effect of the segmentation stage on the overall
classification accuracy. The automated segmentation method was
quantitatively compared with manual segmentation by two expert
radiologists (111 and 112) using three similarity or distance measures
on a data set of 100 masses. The area overlap measures between R1 and
R2, the computer and R1, and the computer and R2 were 0.76 +/- 0.13,
0.74 +/- 0.11, and 0.74 +/- 0.13, respectively. The interobserver
difference in these measures between the two radiologists was compared
with the corresponding differences between the computer and the
radiologists. Using three similarity measures and data from two
radiologists, a total of six statistical tests were performed. The
difference between the computer and the radiologist segmentation was
significantly larger than the interobserver variability in only one
test. Two sets of texture, morphological, and spiculation features, one
based on the computer segmentation, and the other based on radiologist
segmentation, were extracted from a data set of 249 films from 102
patients. A classifier based on stepwise feature selection and linear
discriminant analysis was trained and tested using the two feature
sets. The leave-one-case-out method was used for data sampling. For
case-based classification, the area A(x) under the receiver operating
characteristic (ROC) curve was 0.89 and 0.88 for the feature sets based
on the radiologist segmentation and computer segmentation,
respectively. The difference between the two ROC curves was not
statistically significant.
|
675. | Ben-Arie, J, and Wang, ZQ, "Hierarchical shape description and similarity-invariant recognition using gradient propagation," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 15, pp. 1251-1261, 2001.
Abstract:
This paper presents a novel hierarchical shape description scheme based
on propagating the image gradient radially. This radial propagation is
equivalent to a vectorial convolution with sector elements. The
propagated gradient field collides at centers of convex/concave shape
components, which can be detected as points of high directional
disparity. A novel vectorial disparity measure called Cancellation
Energy is used to measure this collision of the gradient field, and
local maxima of this measure yield feature tokens. These feature tokens
form a compact description of shapes and their components and indicate
their central locations and sizes. In addition, a Gradient Signature is
formed by the gradient field that collides at each center, which is
itself a robust and size-independent description of the corresponding
shape component. Experimental results demonstrate that the shape
description is robust to distortion, noise and clutter. An important
advantage of this scheme is that the feature tokens are obtained
pre-attentively, without prior understanding of the image. The
hierarchical description is also successfully used for
similarity-invariant recognition of 2D shapes with a multidimensional
indexing scheme based on the Gradient Signature.
|
676. | Han, C, Hatsukami, TS, Hwang, JN, and Yuan, C, "A fast minimal path active contour model," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 865-873, 2001.
Abstract:
A new minimal path active contour model for boundary extraction is
presented. Implementing the new approach requires four steps
1) users place some initial end points on or near the desired boundary
through an interactive interface;
2) potential searching window is defined between two end points;
3) graph search method based on conic curves is used to search the
boundary;
4) "wriggling" procedure is used to calibrate the contour and reduce
sensitivity of the search results on the selected initial end points.
The last three steps are performed automatically. In the proposed
approach, the potential window systematically provides a new node
connection for the later graph search, which is different from the
row-by-row and column-by-column methods used in the classical graph
search. Furthermore, this graph search also suggests ways to design a
"wriggling" procedure to evolve the contour in the direction nearly
perpendicular to itself by creating a list of displacement vectors in
the potential window. The proposed minimal path active contour model
speeds up the search and reduces the "metrication error" frequently
encountered in the classical graph search methods e,g,, the dynamic
programming minimal path (DPMP) method.
|
677. | Cohen, LD, and Deschamps, T, "Multiple contour finding and perceptual grouping as a set of energy minimizing paths," ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 2134, pp. 560-575, 2001.
Abstract:
We address the problem of finding a set of contour curves in an image.
We consider the problem of perceptual grouping and contour completion,
where the data is a set of points in the image. A new method to find
complete curves from a set of contours or edge points is presented. Our
approach is an extension of previous work on finding a set of contours
as minimal paths between end points using the fast marching algorithm.
Given a set of key points, we find the pairs of points that have to be
linked and the paths that join them. We use the saddle points of the
minimal action map. The paths are obtained by backpropagation from the
saddle points to both points of each pair.
We also propose an extension of this method for contour completion
where the data is a set of connected components. We find the minimal
paths between each of these components, until the complete set of these
"regions" is connected. The paths are obtained using the same
backpropagation from the saddle points to both components.
|
678. | Yanai, K, and Deguchi, K, "A multi-resolution image understanding system based on multi-agent architecture for high-resolution images," IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, vol. E84D, pp. 1642-1650, 2001.
Abstract:
Recently a high-resolution image that has more than one million pixels
is available easily. However, such an image requires much processing
time and memory for an image understanding system. In this paper, we
propose an integrated image understanding system of multi-resolution
analysis and multiagent-based architecture for high-resolution images.
The system we propose in this paper has capability to treat with a
high-resolution image effectively without much extra cost. We
implemented an experimental system for images of indoor scenes.
|
679. | Yoo, SK, Wang, G, Rubinstein, JT, and Vannier, MW, "Semiautomatic segmentation of the cochlea using real-time volume rendering and regional adaptive snake modeling," JOURNAL OF DIGITAL IMAGING, vol. 14, pp. 173-181, 2001.
Abstract:
The human cochlea in the inner ear is the organ of hearing.
Segmentation is a prerequisite step for 3-dimensional modeling and
analysis of the cochlea. It may have uses in the clinical practice of
otolaryngology and neuroradiology, as well as for cochlear implant
research. In this report, an interactive, semiautomatic, coarse-to-fine
segmentation approach is developed on a personal computer with a
real-time volume rendering board. In the coarse segmentation,
parameters, including the intensity range and the volume of interest,
are defined to roughly segment the cochlea through user interaction. In
the fine segmentation, a regional adaptive snake model designed as a
refining operator separates the cochlea from other anatomic structures.
The combination of the image information and expert knowledge enables
the deformation of the regional adaptive snake effectively to the
cochlear boundary, whereas the real-time volume rendering provides
users with direct 3-dimensional visual feedback to modify intermediate
parameters and finalize the segmentation. The performance is tested
using spiral computed tomography (CT) images of the temporal bone and
compared with the seed point region growing with manual modification of
the commercial Analyze software. Our method represents an optimal
balance between the efficiency of automatic algorithm and the accuracy
of manual work. Copyright (C) 2001 by WB. Saunders Company.
|
680. | Montagnat, J, Delingette, H, and Ayache, N, "A review of deformable surfaces: topology, geometry and deformation," IMAGE AND VISION COMPUTING, vol. 19, pp. 1023-1040, 2001.
Abstract:
Deformable models have raised much interest and found various
applications in the fields of computer vision and medical imaging. They
provide an extensible framework to reconstruct shapes. Deformable
surfaces, in particular, are used to represent 3D objects. They have
been used for pattern recognition [Computer Vision and Image
Understanding 69(2) (1998) 201; IEEE Transactions on Pattern Analysis
and Machine Intelligence 19(10) (1997) 1115], computer animation [ACM
Computer Graphics (SIGGRAPH'87) 21(4) (1987) 205], geometric modelling
[Computer Aided Design (CAD) 24(4) (1992) 178], simulation [Visual
Computer 16(8) (2000) 437], boundary tracking [ACM Computer Graphics
(SIGGRAPH'94) (1994) 185], image segmentation [Computer Integrated
Surgery, Technology and Clinical Applications (1996) 59; IEEE
Transactions on Medical Imaging 14 (1995) 442; Joint Conference on
Computer Vision, Virtual Reality and Robotics in Medicine
(CVRMed-MRCAS'97) 1205 (1997) 13; Medical Image Computing and
Computer-Assisted Intervention (MICCAI'99) 1679 (1999) 176; Medical
Image Analysis 1(1) (1996) 19], etc. In this paper we propose a survey
on deformable surfaces. Many surface representations have been proposed
to meet different 3D reconstruction problem requirements. We classify
the main representations proposed in the literature and we study the
influence of the representation on the model evolution behavior,
revealing some similarities between different approaches. (C) 2001
Elsevier Science B.V. All rights reserved.
|
681. | Chen, CM, Lu, HHS, and Hsiao, AT, "A dual-snake model of high penetrability for ultrasound image boundary extraction," ULTRASOUND IN MEDICINE AND BIOLOGY, vol. 27, pp. 1651-1665, 2001.
Abstract:
Most deformable models require the initial contour to be placed close
to the boundary of the object of interest for boundary extraction of
ultrasound (US) images, which is impractical in many clinical
applications. To allow a distant initial contour, a new dual-snake
model promising high penetrability through the interference of the
noises is proposed in this paper. The proposed dual-snake model
features a new far-reaching external force, called the discrete
gradient flow, a connected component-weighted image force, and an
effective stability evaluation of two underlying snakes. The
experimental results show that, with a distant initial contour, the
mean distance from the derived boundary to the desired boundary is less
than 1.4 pixels, and most snake elements are within 2.7 pixels of the
desired boundaries for the synthetic images with CNR greater than or
equal to 1. For the clinical US images, the mean distance is less than
1.9 pixels, and most snake elements are within 3 pixels of the desired
boundaries. (E-mail: chung@lotus.mc.ntu.edu.tw) (C) 2002 World
Federation for Ultrasound in Medicine Biology.
|
682. | Kamijo, S, Ikeuchi, K, and Sakauchi, M, "Segmentations of spatio-temporal images by spatio-temporal Markov random field model," ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 2134, pp. 298-313, 2001.
Abstract:
There have been many successful researches on image segmentations that
employ Markov Random Field model. However, most of them were interested
in two-dimensional MRF, or spatial MRF, and very few researches are
interested in three-dimensional MRF model. Generally,
'three-dimensional' have two meaning, that are spatially
three-dimensional and spatio-temporal. In this paper, we especially are
interested in segmentations of spatio-temporal images which appears to
be equivalent to tracking problem of moving objects such as vehicles
etc. For that purpose, by extending usual two-dimensional MRF, we
defined a dedicated three-dimensional MRF which we defined as
Spatio-Temporal MRF model(S-T MRF). This S-T MRF models a tracking
problem by determining labels of groups of pixels by referring to their
texture and labeling correlations along the temporal axis as well as
the x-y image axes. Although vehicles severely occlude each other in
general traffic images, segmentation boundaries of vehicle regions will
be determined precisely by this S-T MRF optimizing such boundaries
through spatio-temporal images. Consequently, it was proved that the
algorithm has performed 95% success of tracking in middle-angle image
at an intersection and 91% success in low-angle and front-view images
at a highway junction.
|
683. | Golosio, B, Brunetti, A, and Amendolia, SR, "A novel morphological approach to volume extraction in 3D tomography," COMPUTER PHYSICS COMMUNICATIONS, vol. 141, pp. 217-224, 2001.
Abstract:
Extracting a region of interest from volumetric data represents an
important task in the field of digital image analysis. Several
approaches to this problem are proposed in literature. The present
paper affords volume extraction for regions of interest whose
characteristics are not known a-priori. This is the case, for instance,
of cancerous tissues in medical tomography or defects in industrial
tomography. The technique here described allows extraction of
completely arbitrary shapes with a minimum interaction with the user.
The volume of interest is defined through the semi-automatic selection
of a small set of rail contours at different planes. Such contours are
then blended through a morphing technique in order to interpolate the
cutting surface. The overall technique demonstrates to be intuitive,
efficient and robust. Some results are reported where the method has
been applied to micro-tomographic measurements. (C) 2001 Elsevier
Science B.V. All rights reserved.
|
684. | Fortier, MFA, Ziou, D, Armenakis, C, and Wang, S, "Automated correction and updating of road databases from high-resolution imagery," CANADIAN JOURNAL OF REMOTE SENSING, vol. 27, pp. 78-91, 2001.
Abstract:
Our work addresses the correction and update of road map data from
georeferenced aerial images. This task requires the solution of two
underlying problems: the weak positional accuracy of the existing road
location, and the detection Of new roads. To correct the position of
the existing road network location from the imagery, we use an active
contour ('snakes") optimization approach, with a line enhancement
function. The initialization of the snakes is based on a priori
knowledge derived from the existing vector road data coming from the
National Topographic Database of Geomatics Canada, and from line
junctions computed from the image by a new detector developed for this
application. To generate hypotheses for new roads, a road following
algorithm is applied in the image, starting from the line
intersections, which are already in the existing road network.
Experimental results on a georeferenced image of the Edmonton area,
provided by Geomatics Canada, are presented to validate the approach
and to demonstrate the interest of using line junctions in this kind of
application.
|
685. | Baxter, WW, and McCulloch, AD, "In vivo finite element model-based image analysis of pacemaker lead mechanics," MEDICAL IMAGE ANALYSIS, vol. 5, pp. 255-270, 2001.
Abstract:
Background: Fractures of implanted pacemaker leads are currently
identified by inspecting radiographic images without making full use of
a priori known material and structural information. Moreover, lead
designers are unable to incorporate clinical image data into analyses
of lead mechanics. Methods: A novel finite element/active contour
method was developed to quantify the in vivo mechanics of implanted
leads by estimating the distributions of stress, strain, and traction
using biplane videoradiographic images. The nonlinear equilibrium
equations governing a thin elastic beam undergoing 3-D large rotation
were solved using one-dimensional isoparametric finite elements.
External forces based on local image greyscale values were computed
from each pair of images using a perspective transformation governing
the relationship between the image planes. Results: Cantilever beam
forward solution results were within 0.2% of the analytic solution for
a wide range of applied loads. The finite element/active contour model
was able to reproduce the principal curvatures of a synthetic helix
within 3% of the analytic solution and estimates of the helix's
geometric torsion were within 20% of the analytic solution. Applying
the method to biplane videoradiographic images of a lead acutely
implanted in an anesthetized dog resulted in expected variations in
curvature and bending stress between compliant and rigid segments of
the lead. Conclusions: By incorporating knowledge about lead geometric
and material properties, the 3-D finite element/active contour method
regularizes the image reconstruction problem and allows for more
quantitative and automatic assessment of implanted lead mechanics. (C)
2001 Elsevier Science B.V. All rights reserved.
|
686. | Deschamps, T, and Cohen, LD, "Fast extraction of minimal paths in 3D images and applications to virtual endoscopy," MEDICAL IMAGE ANALYSIS, vol. 5, pp. 281-299, 2001.
Abstract:
The aim of this article is to build trajectories for virtual endoscopy
inside 3D medical images, using the most automatic way. Usually the
construction of this trajectory is left to the clinician who must
define some points on the path manually using three orthogonal views.
But for a complex structure such as the colon, those views give little
information on the shape of the object of interest. The path
construction in 3D images becomes a very tedious task and precise a
priori knowledge of the structure is needed to determine a suitable
trajectory. We propose a more automatic path tracking method to
overcome those drawbacks: we are able to build a path, given only one
or two end points and the 3D image as inputs. This work is based on
previous work by Cohen and Kimmel [Int. J. Comp. Vis. 24 (1) (1997) 57]
for extracting paths in 2D images using Fast Marching algorithm.
Our original contribution is twofold. On the first hand, we present a
general technical contribution which extends minimal paths to 3D images
and gives new improvements of the approach that are relevant in 2D as
well as in 3D to extract linear structures in images. It includes
techniques to make the path extraction scheme faster and easier, by
reducing the user interaction.
We also develop a new method to extract a centered path in tubular
structures. Synthetic and real medical images are used to illustrate
each contribution.
On the other hand, we show that our method can be efficiently applied
to the problem of finding a centered path in tubular anatomical
structures with minimum interactivity, and that this path can be used
for virtual endoscopy. Results are shown in various anatomical regions
(colon, brain vessels, arteries) with different 3D imaging protocols
(CT, MR). (C) 2001 Elsevier Science B.V. All rights reserved.
|
687. | Yu, SX, Lee, TS, and Kanade, T, "A hierarchical Markov random field model for figure-ground segregation," ENERGY MINIMIZATION METHODS IN COMPUTER VISION AND PATTERN RECOGNITION, LECTURE NOTES IN COMPUTER SCIENCE, vol. 2134, pp. 118-133, 2001.
Abstract:
To segregate overlapping objects into depth layers requires the
integration of local occlusion cues distributed over the entire image
into a global percept. We propose to model this process using
hierarchical Markov random field (HMRF), and suggest a broader view
that clique potentials in MRF models can be used to encode any local
decision rules. A topology-dependent multiscale hierarchy is used to
introduce long range interaction. The operations within each level are
identical across the hierarchy. The clique parameters that encode the
relative importance of these decision rules are estimated using an
optimization technique called learning from rehearsals based on
2-object training samples. We find that this model generalizes
successfully to 5-object test images, and that depth segregation can be
completed within two traversals across the hierarchy. This
computational framework therefore provides an interesting platform for
us to investigate the interaction of local decision rules and global
representations, as well as to reason about the rationales underlying
some of recent psychological and neurophysiological findings related to
figure-ground segregation.
|
688. | Ray, N, Chanda, B, and Das, J, "A fast and flexible multiresolution snake with a definite termination criterion," PATTERN RECOGNITION, vol. 34, pp. 1483-1490, 2001.
Abstract:
This paper. describes a fast process of parametric snake evolution with
a multiresolution strategy. Conventional parametric evolution method
relies on matrix inversion throughout the iteration intermittently, in
contrast the proposed method relaxes the matrix inversion which is:
costly and time consuming in cases where the resulting snake is
flexible. The proposed method also eliminates the input of snake
rigidity parameters when the snake is flexible. Also, a robust and
definite termination criterion for both conventional and proposed
methods is demonstrated ill this paper. (C) 2001 pattern Recognition
Society. Published by Elsevier Science Ltd. All rights reserved.
|
689. | Gomes, J, and Faugeras, O, "Using the vector distance functions to evolve manifolds of arbitrary codimension," SCALE-SPACE AND MORPHOLOGY IN COMPUTER VISION, PROCEEDINGS, LECTURE NOTES IN COMPUTER SCIENCE, vol. 2106, pp. 1-13, 2001.
Abstract:
We present a novel method for representing and evolving objects of
arbitrary dimension. The method, called the Vector Distance Function
(VDF) method, uses the vector that connects any point in space to its
closest point on the object. It can deal with smooth manifolds with and
without boundaries and with shapes of different dimensions. It can be
used to evolve such objects according to a variety of motions,
including mean curvature. If discontinuous velocity fields are allowed
the dimension of the objects can change. The evolution method that we
propose guarantees that we stay in the class of VDF's and therefore
that the intrinsic properties of the underlying shapes such as their
dimension, curvatures can be read off easily from the VDF and its
spatial derivatives at each time instant. The main disadvantage of the
method is its redundancy: the size of the representation is always that
of the ambient space even though the object we are representing may be
of a much lower dimension. This disadvantage is also one of its
strengths since it buys us flexibility.
|
690. | Liu, ZC, Zhang, ZY, Jacobs, C, and Cohen, M, "Rapid modeling of animated faces from video," JOURNAL OF VISUALIZATION AND COMPUTER ANIMATION, vol. 12, pp. 227-240, 2001.
Abstract:
Generating realistic 3D human face models and facial animations has
been a persistent challenge in computer graphics. We have developed a
system that constructs textured 3D face models from videos with minimal
user interaction. Our system takes images and video sequences of a face
with an ordinary video camera. After five manual clicks on two images
to tell the system where the eye corners, nose top and mouth corners
are, the system automatically generates a realistic looking 3D human
head model and the constructed model can be animated immediately. A
user with a PC and an ordinary camera can use our system to generate
his/her face model in a few minutes. Copyright (C) 2001 John Wiley
Sons, Ltd.
|
691. | Elmoataz, A, Schupp, S, and Bloyet, D, "Fast and simple discrete approach for active contours for biomedical applications," INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, vol. 15, pp. 1201-1212, 2001.
Abstract:
In this paper, we present a fast and simple discrete approach for
active contours. It is based on discrete contour evolution, which
operates on the boundary of digital shape, by iterative growth
processes on the boundary of the shape. We consider a curve to be the
boundary of a discrete shape, We attach at each point of the boundary a
cost function and deform this shape according to that cost function.
The method presents some advantages. It is a discrete method, which
takes an implicit representation and uses discrete algorithm with a
simple data structure.
|
692. | Tang, M, and Ma, SD, "General scheme of region competition based on scale space," IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 23, pp. 1366-1378, 2001.
Abstract:
In this paper, we propose a general scheme of region competition (GSRC)
for image segmentation based on scale space. First, we present a novel
classification algorithm to cluster the image feature data according to
the generally defined peaks under a certain scale and a scale
space-based classification scheme to classify the pixels by grouping
the resultant feature data clusters into several classes with a
standard classification algorithm. Second, to reduce the resultant
segmentation error, we develop a nonparametric probability model from
which the functional for GSRC is derived. Third, we design a general
and formal approach to automatically determine the initial regions.
Finally, we propose the kernel procedure of GSRC which segments an
image by minimizing the functional. The strategy adopted by GSRC is
first to label pixels whose corresponding regions can be determined in
large likelihood, and then to fine-tune the final regions with the help
of the nonparametric probability model, boundary smoothing, and region
competition. GSRC quantitatively controls the segmentation extent with
the scale space-based classification scheme. Although the description
of the scheme is nonparametric in this paper, GSRC can also work
parametrically if all nonparametric procedures in this paper are
substituted with the parametric counterparts.
|
693. | Hueber, E, Bigue, L, Refregier, P, and Ambs, P, "Optical snake-based segmentation processor with a shadow-casting incoherent correlator," OPTICS LETTERS, vol. 26, pp. 1852-1854, 2001.
Abstract:
What is believed to be the first incoherent snake-based optoelectronic
processor that is able to segment an object in a real image is
described. The process, based on active contours (snakes), consists of
correlating adaptive binary references with the scene image. The
proposed optical implementation of algorithms that are already
operational numerically opens attractive possibilities for faster
processing. Furthermore, this experiment has yielded a new, versatile
application for optical processors. (C) 2001 Optical Society of America.
|
694. | Wang, ZQ, and Ben-Arie, J, "Detection and segmentation of generic shapes based on affine modeling of energy in eigenspace," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 1621-1629, 2001.
Abstract:
This paper presents a novel approach for detection and segmentation of
man made generic shapes in cluttered images. The set of shapes to be
detected are members of affine transformed versions of basic geometric
shapes such as rectangles, circles etc. The shape set is represented by
its vectorial edge map transformed over a wide range of affine
parameters. We use vectorial boundary instead of regular boundary to
improve robustness to noise, background clutter and partial occlusion.
Our approach consists of a detection stage and a verification stage. In
the detection stage, we first derive the energy from the principal
eigenvectors of the set. Next, an a posteriori probability map of
energy distribution is computed from the projection of the edge map
representation in a vectorial eigen-space. Local peaks of the posterior
probability map are located and indicate candidate detections. We use
energy/probability based detection since we find that the underlying
distribution is not Gaussian and resembles a hypertoroid. In the
verification stage, each candidate is verified using a fast search
algorithm based on a novel representation in angle space and the
corresponding pose information of the detected shape is obtained. The
angular representation used in the verification stage yields better
results than a Euclidean distance representation. Experiments are
performed in various interfering distortions, and robust detection and
segmentation are achieved.
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695. | Tsap, LV, Goldgof, DB, and Sarkar, S, "Fusion of physically-based registration and deformation modeling for nonrigid motion analysis," IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 10, pp. 1659-1669, 2001.
Abstract:
In our previous work, we used finite element models to determine
nonrigid motion parameters and recover unknown local properties of
objects given correspondence data recovered with snakes or other
tracking models. In this paper, we present a novel multiscale approach
to recovery of nonrigid motion from sequences of registered intensity
and range images. The main idea of our approach is that a finite
element (FEM) model incorporating material properties of the object can
naturally handle both registration and deformation modeling using a
single model-driving strategy. The method includes a multiscale
iterative algorithm based on analysis of the undirected Hausdorff
distance to recover correspondences. The method is evaluated with
respect to speed and accuracy. Noise sensitivity issues are addressed.
Advantages of the proposed approach are demonstrated using man-made
elastic materials and human skin motion. Experiments with regular grid
features are used for performance comparison with a conventional
approach (separate snakes and FEM models). It is shown, however, that
the new method does not require a sampling/correspondence template and
can adapt the model to available object features. Usefulness of the
method is presented not only in the context of tracking and motion
analysis, but also for a burn scar detection application.
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696. | Lamard, M, and Cochener, B, "Modeling the eye with a view to refractive surgery simulation," JOURNAL FRANCAIS D OPHTALMOLOGIE, vol. 24, pp. 813-822, 2001.
Abstract:
Purpose: To achieve three-dimensional modelizing of the eyeball
(morphological and mechanical behavior) in order to simulate the impact
of various refractive surgery techniques and to study the normal and
pathological states of the eye.
Method: Rebuilding the ocular shell is based on different kinds of
imaging (MR[, ultrasound) including information provided by video
topography. Image data are treated using suitable numerized filters
that allow automatic segmentations of ocular globus edges.
Reconstruction is based on specific mathematical functions (B-splines).
The mechanical behavior of a reconstructed model is simulated by
solving equations of linearized elasticity with the finited elements
method.
Results: Numerous simulations mimed different refractive surgical
techniques and, then validated the model. In addition, simulations of
various pathologies allowed us to verify certain clinical hypotheses.
Conclusion: This work, although still experimental, demonstrates the
advantages of such simulations and will allow novice physicians an
easier approach to different surgical techniques and will help them
understand their effect. Furthermore, it might be useful for simulation
of new surgical concepts even before their in vivo evaluation.
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697. | Liu, RJ, and Yuan, BZ, "Automatic eye feature extraction in human face images," COMPUTING AND INFORMATICS, vol. 20, pp. 289-301, 2001.
Abstract:
This paper presents a fuzzy-based method to extract the eye features in
a head-shoulder image with plain background. This method is comprised
of two stages, namely the face region estimation and the eye features
extraction. In the first stage, a region growing method is adopted to
estimate the face region. In the second stage, the coarse eye area is
firstly determined based on the location of the nasion, then the
deformable template algorithm is completed in two steps to extract the
features of the eyes. Experimental results show the efficiency and
robustness of this method.
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698. | Mishra, A, Dutta, PK, and Ghosh, MK, "Non-rigid cardiac motion quantification from 2D image sequences based on wavelet synthesis," IMAGE AND VISION COMPUTING, vol. 19, pp. 929-939, 2001.
Abstract:
Motion quantification from 2D sequential cardiac images has been
performed on axial images of the left ventricle (LV) obtained from two
different imaging modalities (MRI and Echocardiography images). The
detail point wise motion vectors were evaluated by establishing shape
correspondence between the consecutive contours after reconstructing
curvature information by wavelet synthesis filters at multiple levels.
We present a simple approach that optimizes the shape correspondence
taking the non-uniform contour variation in to account. The shape
matching is done by maximizing the correlation between the
approximation coefficient vectors at certain levels. The algorithm has
been tested over sets of 2D images and the results are compared with
that obtained from a bending energy model. Some experimental results
have also been presented for validation of the algorithm. (C) 2001
Elsevier Science B.V. All rights reserved.
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699. | Schoepflin, T, Chalana, V, Haynor, DR, and Kim, Y, "Video object tracking with a sequential hierarchy of template deformations," IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, vol. 11, pp. 1171-1182, 2001.
Abstract:
We have developed a new contour-based tracking algorithm that uses a
sequence of template deformations to model and track generic video
objects. We organize the deformations into a hierarchy: globally affine
deformations, piecewise (locally) affine deformations, and arbitrary
smooth deformations (snakes). This design enables the algorithm to
track objects whose pose and shape change in time compared to the
template. If the object is not a rigid body, we model the temporal
evolution of its shape by updating the entire template after each video
frame; otherwise, we only update the pose of the object. Experimental
results demonstrate that our method is able to track a variety of video
objects, including those undergoing rapid changes. We quantitatively
compare our algorithm with its constituent pieces (e.g., the snake
algorithm) and show that the complete algorithm can track objects with
moving parts for a longer duration than partial versions of the
hierarchy. It could be benefited from a higher level algorithm to
dynamically adjust the parameters and template deformations to improve
the segmentation accuracy further. The hierarchical nature of this
algorithm provides a framework that offers a modular approach for the
design and enhancement of future object-tracking algorithms.
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700. | Velasco, FA, and Marroquin, JL, "Robust parametric active contours: the Sandwich Snakes," MACHINE VISION AND APPLICATIONS, vol. 12, pp. 238-242, 2001.
Abstract:
Snakes are active contours that minimize an energy function. We present
a new kind of active contours called "Sandwich Snakes". They are formed
by two snakes, one inside and the other outside of the curve that one
is looking for. They have the same number of particles, which are
connected in one-to-one correspondence. At the minimum the two snakes
have the same position. We also present here a multi-scale system,
where Sandwich Snakes are adjusted at increasing resolutions, and an
interactive tool that permits one to easily specify the initial
position for the Sandwich Snakes. Sandwich Snakes exhibit very good
perfomance detecting contours with complex shapes, where the
traditional methods fail. They are also very robust with respect to
noise.
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701. | Angelini, ED, Laine, AF, Takuma, S, Holmes, JW, and Homma, S, "LV volume quantification via spatiotemporal analysis of real-time 3-D echocardiography," IEEE TRANSACTIONS ON MEDICAL IMAGING, vol. 20, pp. 457-469, 2001.
Abstract:
This paper presents a method of four-dimensional (4-D) (3-D + Time)
space-frequency analysis for directional denoising and enhancement of
real-time three-dimensional (RT3D) ultrasound and quantitative measures
in diagnostic cardiac ultrasound. Expansion of echocardiographic
volumes is performed with complex exponential wavelet-like basis
functions called brushlets, These functions offer good localization in
time and frequency and decompose a signal into distinct patterns of
oriented harmonics, which are invariant to intensity and contrast
range. Deformable-model segmentation is carried out on denoised data
after thresholding of transform coefficients, This process attenuates
speckle noise while preserving cardiac structure location, The
superiority of 4-D over 3-D analysis for decorrelating additive white
noise and multiplicative speckle noise on a 4-D phantom volume
expanding in time is demonstrated, Quantitative validation, computed
for contours and volumes, is performed on in vitro balloon phantoms.
Clinical applications of this spaciotemporal analysis tool are reported
for six patient cases providing measures of left ventricular volumes
and ejection fraction.
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702. | Chen, J, Qi, FH, and Cen, F, "3D image segment method with forecasting capability," JOURNAL OF INFRARED AND MILLIMETER WAVES, vol. 20, pp. 194-198, 2001.
Abstract:
A new 3D image segmentation algorithm was proposed. This algorithm
integrates the improved Active Contour model and a new forecast
algorithm. The forecast algorithm is based on the peculiarity of 3D
images i.e. the deformation of the contour along the space or time axis
is continuous in 3D images. The forecast algorithm analyzes the trend
of the deformation of the contour in the segmented images, then
prognosticates the location and | |