4D segmentation of cardiac data using active surfaces with spatiotemporal shape priors

Studies in Computational Intelligence

Volumn 91, Issue , 2008, Pages 77-100

  Abufadel, Amer ^a   Yezzi, Tony ^a   Schafer, Ronald W ^b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b HEWLETT PACKARD LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 40449102461     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-76831-9_4     Document Type: Article

References (20)

1. Merriam-Webster's Medical Dictionary. Merriam-Webster Inc., 2002
2. J. Bland and D. Altman. Statistical methods for assessing agreement between two methods of clinical measurements. Lancet, pages 307-310, 1986
3. A. Chakraborty, L.H. Staib, and J.S. Duncan. An integrated approach to boundary finding in medical images. In IEEE Workshop on Biomedical Image Analysis, pages 13-22, 1994
4. T.F. Chan and L.A. Vese. Active contours without edges. IEEE Transactions on Medical Imaging, 10(2):266-277, 2001
5. T.F. Cootes, A. Hill, C. Taylor, and J. Haslam. Use of active shape models for locating structure in medical images. Image and Vision Computing, 12(6):355-366, 1994
6. A. Gupta, L. von Kurowski, A. Singh, D. Geiger, C.-C. Liang, M.-Y. Chiu, L. Adler, M. Haacke, and D. Wilson. Cardiac MR image segmentation using deformable models. In Computers in Cardiology, pages 747-750, 1993
7. T. Kapur, W.E.L. Grimson, R. Kikinis, and W.M. Wells. Enhanced spatial priors for segmentation of magnetic resonance imagery. Medical Image Computing and Computer-Assisted Intervention (MICCAI), pages 457-468, 1998
8. M. Leventon. Statistical models in medical image analysis. PhD thesis, MIT, Cambridge, MA, 2000
9. M. Lorenzo-Valdes, G.I. Sanchez-Ortiz, A. Elkington, R. Mohiaddin, and D. Rueckert. Segmentation of 4d cardiac mr images using a probabilistic atlas and the em algorithm. Medical Image Analysis, 8(3):255-265, 2004
10. S. Osher and J. Sethian. Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics, 79:12-49, 1988
11. L.H. Saib. Prior shape models for boundary finding. In International Symposium on Biomedical Imaging, pages 30-33, 2002
12. J. Sethian. Level Set Methods and Fast Marching Methods, 2nd edn. Cambridge University Press, 1999
13. L.H. Staib and J.S. Duncan. Boundary finding with parametrically deformable models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 14(11):1061-1075, 1992
14. G. Szekely, A. Kelemen, C. Brechbuhler, and G. Gerig. Segmentation of 3D Objects from MRI volume data using constrained elastic deformations of flexible fourier surface models. In CVRMed95, pages 495-505, 1995
15. A. Tasi, A. Yezzi, W.W. III, C. Tempany, D. Tucker, A. Fan, W.E. Grimson, and A. Wilsky. Model-based curve evolution technique for image segmentation. In CVPR, volume 1, pages I-463-I-468, 2001
16. A. Tasi, A. Yezzi, W. Wells, C. Tempany, D. Tucker, A. Fan, W.E. Grimson, and A. Willsky. A shape-based approach to the segmentation of medical imagery using level sets. IEEE Transactions on Medical Imaging, 22(2):137-154, 2003
17. A. Tsai, A. Yezzi, and A. Willsky. Curve evolution implemntation of the mumford-shah functional for imafe segmentation, denoising, interpolations and magnification. IEEE Transactions on Image Processing, 10(8):1169-1186, August 2001
18. A. Tsai, A. Yezzi, and A.S. Willsky. A curve evolution approach to smoothing and segmentation using the mumford-shah functional. In IEEE Conference on Computer Vision and Pattern Recognition, volume 1, pages 119-124, 2000
19. Y. Wang and L.H. Staib. Boundary finding with prior shape and smoothness. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(2):738-743, 2000
20. A. Yezzi, L. Zllei, and T. Kapur. A variational framework for joint segmentation and registration. In Mathematical Methods in Biomedical Image Analysis, pages 44-51, 2001