References

1

A.N. Lieberman, J.L. Weiss, and et al. Two-dimensional echocardiography and infarc size: relationship of regional wall motion and thickening to the extent of myocardial infarction in the dog. Circulation, 63:739, 1981.

2

N.B. Ingels, G.T. Daughters, E.B. Stimson, and et al. Evaluation of methods for quantitating left ventricular segmental wall motion in man using myocardial markers as a standard. Circulation, 61:966, 1980.

3

E. A. Zerhouni, D. M. Parish, W. J. Rogers, A. Yangand, and E. P. Shapiro. Human heart: tagging with MR imaging - a method for noninvasive assessment of myocardial motion. Radiology, 169:59-63, 1988.

4

E.C. Hildreth. Measurement of Visual Motion. MIT Press, Cambridge, 1984.

5

W.G. O'Del, C.C. Moor, W.C. Hunter, and E.R. McVeigh. Displacement field fitting for calculating 3D myocardial deformation from parallel-tagged mr images. Unpublished.

6

A. A. Young and L. Axel. Three-dimensional motion and deformation of the heart wall: estimation with spatial modulation of magnetization - a model-based approach. Radiology, 185:241-247, 1992.

7

S. Kumar and D. Goldgof. Automatic tracking of SPAMM grid and the estimation of deformation parameters from cardiac MR images. IEEE Transactions on Medical Imaging, 13(1):122-132, 1994.

8

T. S. Denney and J. L. Prince. Reconstruction of 3D left ventricular motion from planar tagged cardiac MR images: an estimation theoretic approach. IEEE Trans. Med. Imag., 14(4), 1995.

9

M. A. Guttman, J. L. Prince, and E. R. McVeigh. Tag and contour detection in tagged MR images of the left ventricle, 1992. submitted to IEEE Transactions on Medical Imaging.

10

T. S. Denney Jr. and J. L. Prince. Optimal brightness functions for optical flow estimation of deformable motion. IEEE Transactions on Image Processing, 3(2), March 1994.

11

P. Anandan. A computational framework and an algorithm for the measurement of visual motion. International Journal of Computer Vision, 2:283-310, 1989.

12

S. Androutsellis-Theotokis and J. L. Prince. Experiments in multiresolution motion estimation for multifrequency tagged cardiac MR images. Submitted to ICIP, 1996.

13

B. K. P. Horn and B. G. Schunck. Determining optical flow. Artificial Intelligence, 17:185-203, 1981.

14

S. N. Gupta and J. L. Prince. On well-posed stochastic formulations of optical flow. In Proceedings of the 29th Annual Conference on Information Sciences and Systems, page 481, Baltimore, March 1995.

15

S. N. Gupta and J. L. Prince. On variable brightness optical flow for tagged MRI. In Information Processing in Medical Imaging, pages 323-334, Brest, June 1995.

16

S. N. Gupta and J. L. Prince. Stochastic formulations of optical flow algorithms under variable brightness conditions. In Proceedings of IEEE International Conference on Image Processing, volume III, pages 484-487, Washington D.C., October 1995.

17

S. N. Gupta and J. L. Prince. Stochastic models for div-curl optical flow methods. IEEE Signal Processing Letters, 3(2):32-35, 1996.

18

J. L. Prince and E. R. McVeigh. Motion estimation from tagged MR image sequences. IEEE Transactions on Medical Imaging, 11(2), June 1992.

19

M. A. Gennert and S. Negahdaripour. Relaxing the brightness constancy assumption in computing optical flow. Technical Report Memo No. 975, MIT Artificial Intelligence Laboratory, June 1987.

20

C.-C. J. Kuo, B. C. Levy, and B. R. Musicus. A local relaxation method for solving elliptic PDEs on mesh-connected arrays. SIAM J. Sci. Stat. Comput., 8(4):550-573, 1987.

21

D. Suter. Motion estimation and vector splines. In Proceedings of CVPR94, pages 939-948, Seattle, 1994.

22

P.M. Morse and H. Feshbach. Methods of Theoretical Physics. McGraw-Hill Book Company, New York, 1953.

23

D. Suter. Vector splines in computer vision. Submitted: Australasian Workshop on Thin-plates, Sydney, Feb 18, 1994.

24

L. Amodei and M. N. Benbourhim. A vector spline approximation. Journal of Approximation Theory, 67:51-79, 1991.

25

M. B. Adams, A. S. Willsky, and B. C. Levy. Linear estimation of boundary value stochastic processes - part I: The role and construction of complementary models. IEEE Transactions on Automatic Control, AC-29(9):803-810, September 1984.

26

A. Rougee, B. C. Levy, and A. S. Willsky. Optic flow estimation inside a bounded domain. Technical Report Technical Report LIDS-P-1589, MIT Laboratory for Information and Decision Systems, 1986.

27

S. N. Gupta and J. L. Prince. On div-curl regularization for motion estimation in 3d volumetric imaging. Submitted to ICIP-96.

28

H.-H. Nagel. On the estimation of optical flow: Relations between different approaches and some new results. Artificial Intelligence, 33:299-324, 1987.