Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2878, Issue , 2003, Pages 440-450

  Lorenzo Valdes M ^a   Sanchez Ortiz, G I ^a   Mohiaddin, R ^b   Rueckert, D ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b ROYAL BROMPTON AND HAREFIELD NHS FOUNDATION TRUST   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BIOLOGICAL ORGANS; CARDIOVASCULAR SYSTEM; IMAGE QUALITY; MAGNETIC RESONANCE IMAGING; MARKOV PROCESSES; MEDICAL IMAGING;

ACTIVE APPEARANCE MODELS (AAM); BLURRING; EXPECTATION MAXIMIZATION (EM) ALGORITHMS; SPATIAL INFORMATION;

IMAGE SEGMENTATION;

EID: 0345255015     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-39899-8_55     Document Type: Article

References (15)

1. J. S. Suri. Computer vision, pattern recognition and image processing in left ventricle segmentation: The last 50 years. Pattern Analysis and Applications, 3(3): 209-242, 2002.
2. F. Vincent, P. Clarysse, P. Croiselle, and I. Magnin. Segmentation of the heart from MR image sequences using a 3D active model. Annals of Biomedical Engineering, 28(1): S-42, 2000.
3. B.P.F. Lelieveldt, R.J. Van der Geest, R.M. Ramze, J.G. Bosch, and J.H.C. Reiber. Anatomical model matching with fuzzy implicit surfaces for segmentation of thoracic volume scans. IEEE Transactions on Medical Imaging, 18(3): 218-230, 1999.
4. M. Lorenzo-Valdes, G. I. Sanchez-Ortiz, R. Mohiaddin, and D. Rueckert. Atlas-based segmentation and tracking of 3D cardiac MR images using non-rigid registration. In Fifth Int. Conf. on Medical Image Computing and Computer-Assisted Intervention (MICCAI '02), Lecture Notes in Computer Science, pages 642-650. Springer-Verlag, 2002.
5. S.C. Mitchell, B.P.F. Lelieveldt, R.J. Van Der Geest, H. G. Bosch, J.H.C. Reiber, and M. Sonka. Multistage hybrid active appearance model matching: Segmentation of left and right ventricles in cardiac MR images. IEEE Transactions on Medical Imaging, 20: 415-423, 2001.
6. S.C. Mitchell, B.P.F. Lelieveldt, J. G. Bosch, R. Van Der Geest, J.H.C. Reiber, and M. Sonka. Segmentation of cardiac MR volume data using 3D active appearance models. In SPIE Conference on Medical Imaging, Image Processing, pages 433-443, 2002.
7. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. Journal Royal Statistical Society A, 39: 1-38, 1977.
8. W. M. Wells III, W. E. L. Grimson, R. Kikinis, and F. A. Jolesz. Adaptive segmentation of MRI data. IEEE Transactions on Medical Imaging, 15(4): 429-442, 1996.
9. Z. Liang, J. R. MacFall, and D. P. Harrington. Parameter estimation and tissue segmentation from multispectral MR images. IEEE Transactions on Medical Imaging, 13(3): 441-449, 1994.
10. K. Van Leemput, F. Maes, D. Vandermeulen, and P. Suetens. Automated model-based tissue classification of MR images of the brain. IEEE Transactions on Medical Imaging, 18(10): 897-908, 1999.
11. Y. Zhang, M. Brady, and S. Smith. Segmentation of brain MR images through a hidden markov random field model and the expectation-maximization algorithm. IEEE Transactions on Medical Imaging, 20: 45-57, 2001.
12. S. Z. Li. Markov Random Field Modeling in Computer Vision. Springer-Verlag, Berlin, Germany, 1995.
13. D. Perperidis, A. Rao, M. Lorenzo-Valdes, R. Mohiaddin, and D. Rueckert. Spatio-temporal alignment of 4D cardiac MR images. In FIMH Conference on Functional Imaging and Modeling of the Heart, 2003. In press.
14. S.P. Raya and J.K. Udipa. Shape-based interpolation of multidimensional objects. IEEE Transactions on Medical Imaging, 9(1): 32-42, 1990.
15. C. Studholme, D.L.G. Hill, and D.J. Hawkes. Automated three-dimensional regisration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. Medical Physics, 24(1): 71-86, 1997.