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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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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).
|
| 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.
|
| 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.
|
| 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.
|
|
| |
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
|
| 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.
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| 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 measur | |