| | This Article | |
| |
| |
| | Share | |
| |
| |
| | Bibliographic References | |
| |
| |
| | Add to: | |
| |
 Digg
 Furl
 Spurl
 Blink
 Simpy
 Google
 Del.icio.us
 Y!MyWeb
| |
| | Search | |
| |
| |
| | |
A Coarse-to-Fine Deformable Contour Optimization Framework
February 2003 (vol. 25 no. 2)
pp. 174-186
Abstract—This paper introduces a novel coarse-to-fine deformable contour optimization framework, which is composed of two main components. The first component uses scale-space and information theories to produce a coarser representation of the input image to be used in a coarse-to-fine optimization scheme. The employment of information theory ensures that maximal image information is propagated to the coarse images and employment of scale spaces provides a mechanism to change the image coarseness locally based on the deformable contour model definition. The second component of this framework uses a novel combination of dynamic programming and gradient descent methods to optimize the contour energy on coarser representations and then use the obtained coarse contour positions in finer optimizations. The motivation in using a combination of dynamic programming and gradient descent method is to take advantage of each method's efficiency and avoid their drawbacks. In order to verify the performance of this framework, we constructed a deformable contour model for the spatiotemporal tracking of closed contours and optimized the model energy under this framework. Experiments on this system performed using synthetic images and real world echocardiographic sequences demonstrated the effectiveness and practicality of this framework.
[1] 174 Y.S. Akgul, “Spatiotemporal Analysis of Deformable Contours,” PhD thesis, Dept. of Computer and Information Sciences, Univ. of Delaware, 2000.[2] Y.S. Akgul and C. Kambhamettu, “A New Multi-Level Framework for Deformable Contour Optimization,” IEEE Computer Vision and Pattern Recognition, vol. II, pp. 465-470, 1999.[3] YS. Akgul and C. Kambhamettu, “A Scale-Space Based Approach for Deformable Contour Optimization,” Scale-Space Theories in Computer Vision, pp. 410-422, Springer, 1999.[4] Y.S. Akgul, C. Kambhamettu, and M. Stone, “Analysis of the Tongue Surface Movement Using a Spatiotemporally Coherent Deformable Model,” Proc. IEEE Workshop Applications of Computer Vision, pp. 109-114, 1998.[5] Y.S. Akgul, C. Kambhamettu, and M. Stone, “Extraction and Tracking of the Tongue Surface from Ultrasound Image Sequences,” IEEE Computer Vision and Pattern Recognition, pp. 298-303, 1998.[6] A.A. Amini,T.E. Weymouth,, and R.C. Jain,“Using dynamic programming for solving variational problems in vision,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 9, pp. 855-867, 1990.[7] P.J. Burt and E.H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. Comm., vol. 31, no. 4, pp. 532-540, 1983.[8] A. Chakraborty, L.H. Staib, and J.S. Duncan, Deformable Boundary Finding in Medical Images by Integrating Gradient and Region Information IEEE Trans. Medical Imaging, vol. 15, pp. 859-870, 1996.[9] V. Chalana and Y. Kim, “A Methodology for Evaluation of Boundary Detection Algorithms on Medical Images,” IEEE Trans. Medical Imaging, vol. 16, no. 6, pp. 642-652, 1997.[10] S. Chandran and A.K. Potty, “Energy Minimization of Contours Using Boundary Conditions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 5, pp. 546-549, May 1998.[11] L. D. Cohen,“On active contour models and balloons,” Computer Vision, Graphics, and Image Processing, vol. 53, No. 2, pp. 211-218, March 1991.[12] L.D. Cohen and I. Cohen, “Finite-Element Methods for Active Contour Models and Balloons for 2D and 3D Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp. 1,131-1,147, Nov. 1993.[13] M.B. Jose Dias and M.N. Jose Leitao, “Wall Position and Thickness Estimation from Sequences of Echocardiographis Images,” IEEE Trans. Medical Imaging, vol. 15, pp. 25-38, 1996.[14] M.P. Dubuisson-Jolly, C.C. Liang, and A. Gupta, “Optimal Polyline Tracking for Artery Motion Compensation in Coronary Angiography,” Proc. Int'l Conf. Computer Vision, pp. 414-419, 1998.[15] D. Geiger, A. Gupta, L.A. Costa, and J. Vlontzos, Dynamical Programming for Detecting, Tracking and Matching Deformable Contours IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 3, pp. 294-302, Mar. 1995.[16] D. Geiger and J. Kogler,“Scaling images and image features via the renormalization group,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, 1993.[17] S.R. Gunn and M.S. Nixon, “A Robust Snake Implementation; A Dual Active Contour,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, pp. 63-68, 1997.[18] A. Hammoude, “Endocardial Border Identification in Two-Dimensional Echocardiographic Images: Review of Methods,” Computerized Medical Imaging and Graphics, vol. 22, pp. 181-193, 1998.[19] J. Ivins and J. Porrill, “Active-Region Models for Segmenting Textures and Colors,” Image and Vision Computing, vol. 13, no. 5, pp. 431-438, June 1995.[20] G. Jacob, J.A. Noble, C. Behrenbruch, A.D. Kelion, and A.P. Banning, “A Shape-Space-Based Approach to Tracking Mycordial Borders and Quantifying Regional Left-Ventricular Function Applied in Echocardiography,” IEEE Trans. Medical Imaging, vol. 21, no. 3, pp. 226-238, 2002.[21] M. Jägersand, “Saliency Maps and Attention Selection in Scale and Spatial Coordinates: An Information Thoretic Approach,” Proc. Fifth Int'l Conf. Computer Vision, pp. 195-202, 1995.[22] R. Jain, R. Kasturi, and B.G. Schunck, Machine Vision. New York: McGraw-Hill, 1995.[23] M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models,” Proc. Int'l Conf. Computer Vision, pp. 259-269, 1987.[24] A. Klinger, “Pattern and Search Statistics,” Optimizing Methods in Statistics, J.S. Rustagi, ed. Academic Press, 1971.[25] J.J. Koenderink, “The Structure of Images,” Biological Cybernetics, vol. 50, pp. 363-370, 1984.[26] A.S.E. Koster, K.L. Vincken, C.N. DeGraaf, O.C. Zander, and M.A. Viergever, “Heuristic Linking Models in Multiscale Image Segmentation,” Computer Vision and Image Understanding, vol. 65, no. 3, pp. 382-402, Mar. 1997.[27] K.F. Lai and R.T. Chin, "Deformable Contours—Modeling and Extraction," Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 11, pp. 1,084-1,090, 1995.[28] T. Lindeberg, Scale-Space Theory in Computer Vision. Kluwer Academic, 1994.[29] O. Musse, F. Heitz, and J.P. Armspach, “Topology Preserving Deformable Image Matching Using Constrained Hierarchical Parametric Models,” IEEE Trans. Image Processing, vol. 10, no. 7, pp. 1081-1093, July 2001.[30] W.J. Niessen, K.L. Vincken, A.S.E. Koster, and M.A. Viergever, "A Comparison of Multiscale Image Representations for Image Segmentation," IEEE Workshop Math. Methods in Biomedical Image Analysis,San Franciso, Calif., pp. 263-272, 1996.[31] W.J. Niessen, K.L. Vincken, J.A. Weickert, and M.A. Viergever, “Nonlinear Multiscale Representations for Image Segmentation,” Computer Vision and Image Understanding, vol. 66, no. 2, pp. 233-245, May 1997.[32] J.-Y. Park, T. McInerney, D. Terzopoulos, and M.-H. Kim, “A Non-Self-Intersecting Adaptive Deformable Surface for Complex Boundary Extraction from Volumetric Images,” Computers and Graphics, vol. 25, no. 3, pp. 421-440, 2001.[33] R. Ronfard, “Region-Based Strategies for Active Contour Models,” Int'l J. Computer Vision, vol. 13, no. 2, 1994.[34] E. Sharon, A. Brandt, and R. Basri, Segmentation and Boundary Detection Using Multiscale Intensity Measurements Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, 2001.[35] L.V. Tsap, D.B. Goldgof, and S. Sarkar, “Multiscale Combination of Physically-Based Registration and Deformation Modeling,” IEEE Computer Vision and Pattern Recognition, pp. 422-429, 2000.[36] K.L. Vincken, W.J. Niessen, and M.A. Viergever, "Blurring Strategies for Image Segmentation Using a Multiscale Linking Model," IEEE Conf. Computer Vision and Pattern Recognition, CVPR '96,San Francisco, Calif., pp. 21-26, IEEE CS Press, 1996.[37] G.Q. Wei, J.Z. Qian, and H. Schramm, “Generalized Dynamic Programming Approaches for Object Detection: Detecting Spine Boundaries and Vertebra Endplates,” Proc. Computer Vision and Pattern Recongition, pp. 954-959, 2001.[38] A.P. Witkin, “Scale-Space Filtering,” Proc. Int'l Joint Conf. Artificial Intelligence, pp. 1019-1022, 1983.[39] C. Raphael, “Coarse-to-Fine Dynamic Programming,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 12, pp. 1379-1390, Dec. 2001.
Index Terms:
Deformable models, deformable model energy optimization, coarse-to-fine optimization, dynamic programming, spatiotemporal contour tracking.
Citation:
Yusuf Sinan Akgul, Chandra Kambhamettu, "A Coarse-to-Fine Deformable Contour Optimization Framework," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 2, pp. 174-186, Feb. 2003, doi:10.1109/TPAMI.2003.1177150
