Simultaneous segmentation and registration for functional MR images

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 747-750

  Yunmei, Chen ^a   Thiruvenkadam, Sheshadri ^a   Feng, Huang ^a   Gopinath, Kaundinya S ^b   Brigg, Richard W ^b  

^a UNIVERSITY OF FLORIDA   (United States)

^b UNIVERSITY OF FLORIDA COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; DATA REDUCTION; FEATURE EXTRACTION; MAGNETIC RESONANCE IMAGING; OPTICAL RESOLVING POWER; TIME SERIES ANALYSIS; BRAIN MAPPING; PATTERN RECOGNITION; TIME SERIES;

HIGH RESOLUTION IMAGES; IMAGE INFORMATION; SHAPE MATCHING; SYNTHETIC DATA;

IMAGE SEGMENTATION;

ENERGY FUNCTIONALS; FMRI DATA ANALYSIS; HIGH RESOLUTION IMAGE; IMAGE GRADIENTS; IMAGE INFORMATION; MOTION ARTIFACT; PRIOR KNOWLEDGE; SPATIAL TRANSFORM;

EID: 33751571201     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (22)

1. B. B. Biswal and J. S. Hyde. Contour-based registration technique to differentiate between task-activation and head motion induced signal variations in fmri. Magn Reson Med. 38:470-476, 1997.
2. V. Caselle, F. Catt, T. Coll, and F. Dibos. A geometric model for active contours in image processing. Numerische Mathematik, 66:1-31, 1993.
3. V. Caselles, R. Kimmel, and G. Sapiro. Geodesic active contours. International Journal of Computer Vision, 22(1):61-79, 1997.
4. T. F. Chan and L. A. Vese. Active contours without edges. IEEE Trans. Image Processing, 10(2):266-277, 2001.
5. A. Collignon, F. Maes, D. Vandermeulen, P. Suetens, and G. Marchal. Automated multimodality image registration using information theory. In Info. Processing in medical Images, Brest, France, 1995.
6. D. Cremers, C. Sehn, and J. Weickert. Diffusion-snakes: Combining statistical shape knowledge and image information in a variational framework. Proceedings 1st IEEE Workshop on Variational and Level Set methods in Computer Vision, Vancouver, B.C., Canada, 2001.
7. G. Hermosillo, C. Chefd'Hotel, and O. Faugeras. A variational approach to multi-modal image matching. RR4117 INRIA, 2001.
8. W. W. III, P. Viola, H. A. S. Nakajima, and R. Kikinis. Multi-modal volume registration by maximization of mutual information. Medical Image Analysis, 1(1):35-51, 1996.
9. L. Junck, J. G. Moen, G. D. Hutchins, M. B. Brown, and D. E. Kuhl. Correlation methods for the centering, rotation, and alignment of functional brain images. J. Nucl. Med., 31:1220-1226, 1990.
10. J.West, J. Fitzpatrick, and et al. Comparision and evaluation of retrospective intermodality image registration techniques. 2710 of Proc. SPIE in Medical Imaging: Image Processing, Newport Beach, California, February 1996.
11. M. Kass, A. Witkin, and D. Terzopoulos. Snakes: Active contour models. Inter. Journal of Computer Vision., pages 321-333, 1988.
12. S. Kichenassamy, A. Kumar, and P. Olver. Gradient flows and geometric active contour models. Proc. ICCV'95 IEEE Computer Soc. Press, pages 810-185, 1995.
13. M. E. Leventon, W. E. L. Grimson, and O. Faugeras. Statistical shape influence in geodesic active contours. Proc. IEEE Conf. Comp. Vision and Patt. Recog., pages 316-323, 2000.
14. R. Malladi, J. Sethian, and B. Vemuri. Shape modeling with front propagation: A level set approach. IEEE Trans. Pattern Anal. machine Intell. 17:158-175, 1995.
15. D. Mumford and J. Shah. Optimal approximation by piecewise smooth functions and associated variational problems. Comm. Pure Appl. Math., 42:557-685, 1989.
16. N. Paragios. A variational approach for the segmentation of the left ventricle in MR cardiac images. Proceedings 1st IEEE Workshop on Variational and Level Set methods in Computer Vision, Vancouver, B.C., Canada, 2001.
17. N. Paragios and R. Deriche. Geodesic active regions for supervised texture segmentation. IEEE ICCV Cofu, Greece, 1999.
18. R.P.Woods, J.C.Mazziota, and S.R.Cherry. Mri-pet registration with automated algorithm. J. Comput. Assist. Tomogr, Vol.17:536-546, 1993.
19. P. Thevenaz and M. Unser. Optimization of mutual information for multiresolution image registration. IEEE Trans. on Image Processing, 9(12):2083-2099, Dec. 2000.
20. A. Tsai, J. A. Yezzi, and A. S. Willsky. Curve evolution implementation of the mumford-shah functional for image segmentation, denoising, interpolation, and magnification. IEEE Transactions on Image Processing, 10(8):1169-1186, 2001.
21. P. Viola and W. M. W. III. Alignment by maximization of mutual information. In Intl. Conf. on Compu. Vision, Cambridge, MA, 1996.
22. S. C. Zhu and A. Yuille. Region competition: unifying snakes, region growing. Bayes/MDL for multiband image segmentation, IEEE PAMI, Vol. 18:884-900, 1996.