An optimal control approach for the registration of image time-series

Proceedings of the IEEE Conference on Decision and Control

Volumn , Issue , 2009, Pages 2427-2434

  Niethammer, Marc ^a,b   Hart, Gabriel L ^a   Zach, Christopher ^a  

^a University of North Carolina   (United States)

^b UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; OPTIMIZATION;

DIFFEOMORPHIC IMAGE REGISTRATIONS; EFFICIENT COMPUTATION; IMAGE CORRESPONDENCE; IMAGE TIME-SERIES; LARGE DISPLACEMENTS; NUMERICAL IMPLEMENTATION; OPTIMIZATION PROBLEMS; UNBIASED ESTIMATION;

TIME SERIES;

EID: 77950819394     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2009.5399532     Document Type: Conference Paper

References (29)

1. J. K. Aggarwal and Q. Cai. Human motion analysis: A review. Computer Vision and Image Understanding, 73(3):428-440, 1999.
2. J. K. Aggarwal, Q. Cai, W. Liao, and B. Sabata. Nonrigid motion analysis: Articulated and elastic motion. Computer Vision and Image Understanding, 70(2):142-156, 1998.
3. L. Alvarez, C. A. Castano, M. Garcia, K. Krissian, L. Mazorra, A. Salgado, and J. Sanchez. Symmetric optical flow. In Proceedings of EUROCAST, pages 676-683, 2007.
4. K. A. Bartels, A. C. Bovik, and C. E. Griffin. Spatio-temporal tracking of material shape change via multi-dimensional splines. In Proceedings of the IEEE Workshop on Biomedical Image Analysis, pages 110-116, 1994.
5. M. Beg, M. Miller, A. Trouvé, and L. Younes. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. International Journal of Computer Vision, 61(2):139-157, 2005.
6. M. F. Beg and A. Khan. Symmetric data attachment terms for large deformation image registration. IEEE Transactions on Medical Imaging, 26(9):1179-1189, 2007.
7. L. Bengtsson, M. Ghil, and E. Källen, editors. Dynamic Meteorology: Data Assimilation Methods. Springer, 1981.
8. A. F. Bennett. Inverse Methods in Physical Oceanography. Cambridge University Press, 1992.
9. A. Borzi, K. Ito, and K. Kunisch. Optimal control formulation for determining optical flow. SIAM Journal on Scientific Computing, 24(3):818-847, 2002.
10. A. Bruhn, J. Weickert, and C. Schnörr. Lucas/Kanade meets Horn/Schunck: Combining local and global optical flow methods. International Journal of Computer Vision, 61(3):211-231, 2005.
11. I. Csapo, C. M. Holland, and C. R. G. Guttmann. Image registration framework for large-scale longitudinal MRI data sets: strategy and validation. Magnetic Resonance Imaging, 25:889-893, 2007.
12. G. Evensen. Data Assimilation: The Ensemble Kalman Filter. Springer, 2007.
13. J. Jackson, A. Yezzi, and S. Soatto. Tracking deformable moving objects under severe occlusions. In Proceedings of the Conference on Decision and Control, volume 3, pages 2990-2995. IEEE, 2004.
14. A. R. Khan and M. F. Beg. Representation of time-varying shapes in the large deformation diffeomorphic framework. In Proceedings of the International Symposium of Biomedical Imaging (ISBI), pages 1521-1524. IEEE, 2008.
15. M. J. Ledesma-Carbayo, J. Kybic, M. Desco, A. Santos, M. Sühling, P. Hunziker, and M. Unser. Spatio-temporal nonrigid registration for ultrasound cardiac motion estimation. IEEE Transactions on Medical Imaging, 24(9):1113-1126, 2005.
16. J. L. Lions. Optimal Control Systems Governed by Partial Differential Equations. Springer, 1970.
17. D. S. Marcus, T. H. Wand, J. Parker, J. G. Csernansky, J. C. Morris, and R. L. Buckner. Open access series of imaging studies (OASIS): Cross-sectional mri data in young, middle aged, nondemented, and demented older adults. Journal of Cognitive Neuroscience, 19:1498-1507, 2007.
18. M. Miller. Computational anatomy: shape, growth, and atrophy comparison via diffeomorphisms. Neuroimage, 23:S19-S33, 2004.
19. M. Miller, A. Trouvé, and L. Younes. On the metrics and Euler-Lagrange equations of computational anatomy. Annual Reviews in Biomedical Engineering, 4(1):375-405, 2002.
20. N. Papadakis, T. Corpetti, and E. Mémin. Dynamically consistent optical flow estimation. In Proceedings of the International Conference on Computer Vision (ICCV), pages 1-7, 2007.
21. N. Papadakis and E. Mémin. A variational technique for time consistent tracking of curves and motion. Journal of Mathematical Imaging and Vision, 31(1):81-103, 2008.
22. D. Perperidis, R. H. Mohiaddin, and D. Rueckert. Spatio-temporal free-form registration of cardiac MR image sequences. Medical Image Analysis, 9:441-456, 2005.
23. B. Protas, T. R. Bewley, and G. Hagen. A computational framework for the regularization of adjoint analysis in multiscale PDE systems. Journal of Computational Physics, 195:49-89, 2004.
24. W. Ren, S. Singh, M. Singh, and Y. S. Zhu. State-of-the-art on spatio-temporal information-based video retrieval. Pattern Recognition, 42:267-282, 2009.
25. D. Shen and C. Davatzikos. Measuring temporal morphological changes robustly in brain MR images via 4-dimensional template warping. Neuroimage, 21(4):1508-1517, 2004.
26. G. Sundaramoorthi, A. Yezzi, and A. C. Mennucci. Coarse-to-fine segmentation and tracking using Sobolev active contours. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(5):851-864, 2008.
27. R. Szeliski and J. Coughlan. Spline-based image registration. International Journal of Computer Vision, 22(3):199-218, 1997.
28. A. Veeraraghavan, A. K. Roy-Chowdhury, and R. Chellappa. Matching shape sequences in video with applications in human movement analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(12):1896-1909, 2005.
29. A. J. Yezzi and S. Soatto. Deformotion: Deforming motion, shape average and the joint registration and approximation of structures in images. International Journal of Computer Vision, 53(2):153-167, 2003.