Shape analysis and fuzzy control for 3D competitive segmentation of brain structures with level sets

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

Volumn 3951 LNCS, Issue , 2006, Pages 458-470

  Ciofolo, Cybèle ^a   Barillot, Christian ^a  

^a CAMPUS DE BEAULIEU   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; FUZZY CONTROL; FUZZY SETS; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS;

BRAIN STRUCTURES; FUZZY STATES; SHAPE ANALYSIS;

BRAIN;

EID: 33745871215     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11744023_36     Document Type: Conference Paper

References (20)

1. Osher, S., Sethian, J.A.: Fronts propagating with curvature dependant speed: algorithms based on Hamilton-Jacobi formulation. Jour. Comp. Phys. 79 (1988) 12-49
2. Caselles, V., Kimmel, R., Sapiro, G.: Geodesic active contours. Int. Jour. Comp. Vis. 22 (1997) 61-79
3. Malladi, R., Sethian, J.A., Vemuri, C.: Shape modeling with front propagation: a level set approach. IEEE Trans. Patt. Anal. Mach. Intell. 17 (1995) 158-175
4. Vese, L.A., Chan, T.F.: A multiphase level set framework for image segmentation using the Mumford and Shah model. Int. Jour. Comp. Vis. 50 (2002)
5. Paragios, N.: A variational approach for the segmentation of the left ventricle in cardiac image analysis. Int. Jour. Comp. Vis. 50 (2002) 345-362
6. Paragios, N., Deriche, R.: Geodesic active contours and level sets for the detection and tracking of moving objects. IEEE Trans. Patt. Anal. Mach. Intell. 22 (2000) 266-280
7. Paragios, N., Deriche, R.: Coupled geodesic active regions for image segmentation: a level set approach. In: Eur. Conf. Comp. Vis. (ECCV). (2000) 224-240
8. Cootes, T.F., Taylor, C.J., Cooper, D.H., Graham, J.: Active shape models - their training and application. Comp. Vis. Im. Underst. 61 (1995) 38-59
9. Rousson, M., Paragios, N.: Shape priors for level set representations. In: Eur. Conf. Comp. Vis. (ECCV). (2002) 78-92
10. Tsai, A., et. al.: A shape-based approach to the segmentation of medical imagery using level sets. IEEE Trans. Med. Imag. 22 (2003) 137-154
11. Yang, J., Duncan, J.S.: 3D image segmentation of deformable objects with joint shape-intensity prior models using level sets. Med. Image Anal. 8 (2004) 285-294
12. Xu, D.L., et. al.: Reconstruction of the human cerebral cortex from magnetic resonance images. IEEE Trans. Med. Imag. 18 (1999) 467-480
13. Colliot, O., Camara, O., Dewynter, R., Bloch, I.: Description of brain internal structures by means of spatial relations for MR image segmentation. In: Int. Soc. Opt. Eng. SPIE Med. Imag. (2004) 444-455
14. Ciofolo, C., Barillot, C.: Brain segmentation with competitive level sets and fuzzy control. In: Int. Conf. Inform. Proc. Med. Imag.(IPMI). (2005) 333-344
15. Baillard, C., Hellier, P., Barillot, C.: Segmentation of brain 3D MR images using level sets and dense registration. Med. Image Anal. 5 (2001) 185-194
16. Celeux, G., et. al.: L'algorithme SEM: un algorithme d'apprentissage probabiliste pour la reconnaissance de mélanges de densités. Rev. Stat. App. 34 (1986) 35-51
17. Zhao, H.K., Chan, T., Merriman, B., Osher, S.: A variational level set approach to multiphase motion. Jour. Comp. Phys. 127 (1996) 179-195
18. Samson, C., Blanc-Féraud, L., G., A., Zerubia, J.: A level set model for image classification. Int. Jour. Comp. Vis. 40 (2000) 187-197
19. Borgefors, G.: Distance transformations in digital images. Comp. Vis. Graph. Im. Proc. 34 (1986) 344-371
20. Zijdenbos, A.P., Dawant, B.M., Margolin, R.A., Palmer, A.C.: Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans. Med. Imag. 13 (1994) 716-724