A regions of confidence based approach to enhance segmentation with shape priors

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7533, Issue , 2010, Pages

  Appia, Vikram V ^a   Ganapathy, Balaji ^a   Abufadel, Amer ^b   Yezzi, Anthony ^a   Faber, Tracy ^c  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b Khoury Group   (United States)

^c EMORY UNIVERSITY   (United States)

Author keywords

Active contours; Cardiac MRI segmentation; Curve evolution; Eigenshapes; Image alignment; Principal component analysis; Regions of confidence labels; Regions of interest labels; Shape alignment; Shape priors

Indexed keywords

ACTIVE CONTOURS; CARDIAC MRI; CARDIAC MRI SEGMENTATION; CURVE EVOLUTION; EIGENSHAPES; IMAGE ALIGNMENT; REGIONS OF INTEREST; REGIONS-OF-CONFIDENCE; SHAPE PRIORS;

ALIGNMENT; EDGE DETECTION; INFORMATION USE; LABELS; NATURAL LANGUAGE PROCESSING SYSTEMS; PRINCIPAL COMPONENT ANALYSIS;

IMAGE SEGMENTATION;

EID: 77952041909     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.850888     Document Type: Conference Paper

References (11)

1. Chen, Y., Thiruvenkadam, S., Huang, F., Wilson, D., Md, E. A. G., and Tagare, H. D., "On the incorporation of shape priors into geometric active contours," Variational and Level Set Methods in Computer Vision, IEEE Workshop on 0, 145-152 (2001).
2. Leventon, M., Grimson, E., and Faugeras, O., "Statistical shape influence in geodesic active contours," in [Proc. of Computer Vision and Pattern Recognition CVPR 2000], (2000).
3. Mumford, D. and Shah, J., "Optimal approximations by piecewise smooth functions and associated variational problems," Communications on Pure and Applied Mathematics 42(5), 577-685 (1989).
4. Chan, T. and Vese, L., "An active contour model without edges," in [Int. Conf. Scale-Space Theories in Computer Vision], 141-151 (1999).
5. Chan, T. E. and Vese, L. A., "A level set algorithm for minimizing the mumford-shah functional in image processing," in [IEEE WORKSHOPon Variational and Level Set Methods in Computer Vision], 161168.
6. Cremers, D., Tischhauser, F., Weickert, J., and Schnorr, C., "Diffusion snakes: Introducing statistical shape knowledge into the mumford-shah functional," 50, 295-313 (December 2002). (Pubitemid 35377417)
7. Tsai, A., Yezzi, A., andWillsky, A., "A curve evolution approach to smoothing and segmentation using the mumfordshah functional," I: 119-124 (2000). (Pubitemid 32371396)
8. Tsai, A., Yezzi, A., Wells, W., Tempany, C., Tucker, D., Fan, A., Grimson, W. E., and Willsky, A., "A shape-based approach to the segmentation of medical imagery using level sets.," in [Medical Imaging, IEEE Transactions on], IEEE transactions on medical imaging 22, 137-154 (February 2003).
9. Cremers, D., Sochen, N., and Schnrr, C., "Multiphase dynamic labeling for variational recognition-driven image segmentation," in [In ECCV 2004, LNCS 3024], 74-86, Springer (2004). (Pubitemid 38717175)
10. Osher, S. and Sethian, J. A., "Fronts propagating with curvature dependent speed: Algorithms based on hamilton-jacobi formulations," JOURNAL OF COMPUTATIONAL PHYSICS 79(1), 12-49 (1988).
11. Abufadel, A., Yezzi, T., and Schafer, R., "4d segmentation of cardiac data using active surfaces with spatiotemporal shape priors," Comp Imaging 6498(1), SPIE (2007). (Pubitemid 47320348)