G. Celeux, F. Forbes, and N. Peyrard, EM procedures using mean field-like approximations for Markov model-based image segmentation, Pattern Recognition, vol.36, issue.1, pp.131-144, 2003.
DOI : 10.1016/S0031-3203(02)00027-4

URL : https://hal.archives-ouvertes.fr/inria-00072526

A. Dempster, N. Laird, and D. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. Roy. Statist. Soc. Ser. B, vol.39, pp.1-38, 1977.

F. Forbes, S. Doyle, D. Garcia-lorenzo, C. Barillot, and M. Dojat, A Weighted Multi-Sequence Markov Model For Brain Lesion Segmentation, AISTATS, Sardignia, 2010.
URL : https://hal.archives-ouvertes.fr/inserm-00723808

F. Forbes, S. Doyle, D. García-lorenzo, C. Barillot, and M. Dojat, Adaptive weighted fusion of multiple MR sequences for brain lesion segmentation, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.69-72, 2010.
DOI : 10.1109/ISBI.2010.5490413

URL : https://hal.archives-ouvertes.fr/inserm-00723807

O. Freifeld, H. Greenspan, and J. Goldberger, LESION DETECTION IN NOISY MR BRAIN IMAGES USING CONSTRAINED GMM AND ACTIVE CONTOURS, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.596-599, 2007.
DOI : 10.1109/ISBI.2007.356922

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

D. Garcia-lorenzo, L. Lecoeur, D. L. Arnold, D. L. Collins, and C. Barillot, Multiple Sclerosis Lesion Segmentation Using an Automatic Multimodal Graph Cuts, MICCAI, pp.584-591, 2009.
DOI : 10.1007/978-3-642-04271-3_71

URL : https://hal.archives-ouvertes.fr/inria-00423040

K. Van-leemput, F. Maes, D. Vandermeulen, A. Colchester, and P. Suetens, Automated segmentation of multiple sclerosis lesions by model outlier detection, IEEE Transactions on Medical Imaging, vol.20, issue.8, pp.677-688, 2001.
DOI : 10.1109/42.938237