Robust 3D segmentation of anatomical structures with level sets

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

Volumn 1935, Issue , 2000, Pages 236-245

  Baillard, C ^a   Barillot, C ^a  

^a INRIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; MEDICAL IMAGING; PROBABILITY DENSITY FUNCTION;

3D MEDICAL IMAGE; 3D SEGMENTATION; ADAPTIVE PARAMETERS; ANATOMICAL STRUCTURES; BRAIN MR IMAGES; EVOLUTION MODELING; IMPLICIT FUNCTION; ITERATION STEP;

IMAGE SEGMENTATION;

EID: 84945533150     PISSN: 03029743     EISSN: 16113349     Source Type: Journal    
DOI: 10.1007/978-3-540-40899-4_24     Document Type: Article

References (18)

1. O. Amadieu, E. Debreuve, M. Barlaud, and G. Aubert. Inward and outward curve evolution using level set method. In ICIP, Kobe, Japan, oct. 1999.
2. C. Baillard, P. Hellier, and C. Barillot. Segmentation of 3D brain structures using level sets and dense registration. In IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, jun. 2000.
3. V. Caselles, R. Kimmel, and G. Sapiro. Geodesic active contours. IJCV, 22:61-79, 1997.
4. D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans. Design and construction of a realistic digital brain phantom. IEEE Transactions on Medical Imaging, 17(3):463-468, jun. 1998.
5. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. In Royal Statistical Society, pages 1-38, 1976.
6. J. Gomes and O. Faugeras. Reconciling distance functions and Level-Sets. Technical Report 3666, Inria, apr. 1999.
7. R. Kimmel, N. Kiryati, and A. Bruckstein. Analyzing and synthesizing images by evolving curves with the Osher-Sethian method. IJCV, 24(1):37-55, 1997.
8. L. M. Lorigo, O. Faugeras, W. E. L. Grimson, R. Keriven, and R. Kikinis. Segmentation of bone in clinical knee MRI using texture-based geodesic active contours. In A. Colchester and S. Delp, editors, MICCAI, number 1496 in LNSC, pages 1195-1204, Cambridge, MA, USA, oct. 1998. Springer.
9. R. Malladi, J. A. Sethian, and B. C. Vemuri. Shape modeling with front propagation: A level set approach. IEEE Tr. on PAMI, 17(2):158-175, feb. 1995.
10. M. Mignotte and J. Meunier. Deformable template and distribution mixture-based data modeling for the endocardial contour tracking in an echographic sequence. In CVPR, pages 225-230, jun. 1999.
11. S. Osher and J. A. Sethian. Fronts propagating with curvature dependent speed: Algorithms based on Hamilton-Jacobi formulation. J. of Computational Physics, 79:12-49, 1988.
12. C. Papin, P. Bouthemy, E. Mémin, and G. Rochard. Tracking and characterization of convective clouds from satellite images. In EUMETSAT Meteo. Satellite Data Users Conf., Copenhague, sep. 1999.
13. N. Paragios and R. Deriche. Unifying boundary and region-based information for geodesic active tracking. In CVPR, volume 2, pages 300-305, Fort Collins, Colorado, jun. 1999.
14. N. Paragios and R. Deriche. Video and image sequence analysis - geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Tr. on PAMI, 22(3):266-280, 2000.
15. D. Terzopoulos. Regularization of inverse visual problems involving discontinuities. IEEE Tr. on PAMI, 8(2):413-424, 1986.
16. JH. Van Bemmel and MA. Musen. Handbook of medical informatics. Springer, URL: http://www.mieur.nl/mihandbook, 1997.
17. A. Yezzi, A. Tsai, and A. Willsky. Binary and ternary flows for image segmentation. In ICIP, Kobe, Japan, oct. 1999.
18. X. Zeng, L. H. Staib, R. T. Schultz, H. Tagare, L. Win, and J. S. Duncan. A new approach to 3D sulcal ribbon finding fromMR images. In C. Taylor and A. Colchester, editors, MICCAI, number 1679 in LNSC, pages 148-157. Springer, sep. 1999.