W. Wells, W. Grimson, R. Kikinis, and F. Jolesz, Adaptive segmentation of MRI data, IEEE Transactions on Medical Imaging, vol.15, issue.4, pp.429-471, 1996.
DOI : 10.1109/42.511747

J. Ashburner and K. Friston, Unified segmentation, NeuroImage, vol.26, issue.3, pp.839-51, 2005.
DOI : 10.1016/j.neuroimage.2005.02.018

L. Germond, M. Dojat, C. Taylor, and C. Garbay, A cooperative framework for segmentation of MRI brain scans, Artificial Intelligence in Medicine, vol.20, issue.1, pp.77-93, 2000.
DOI : 10.1016/S0933-3657(00)00054-3
URL : https://hal.archives-ouvertes.fr/inserm-00402412

N. Richard, M. Dojat, and C. Garbay, Distributed Markovian segmentation: Application to MR brain scans, Pattern Recognition, vol.40, issue.12, pp.3467-80, 2007.
DOI : 10.1016/j.patcog.2007.03.019

S. Geman and D. Geman, Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images*, Journal of Applied Statistics, vol.1, issue.5-6, pp.721-762, 1984.
DOI : 10.1109/TIT.1972.1054786

J. Besag, Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986.
DOI : 10.1016/0031-3203(83)90012-2

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.131-175, 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 likehood from incomplete data via EM algorithm, Journal of the Royal Statistical Society, vol.39, pp.1-38, 1977.

B. Scherrer, M. Dojat, F. Forbes, C. Garbay, R. Bellazzi et al., MRF agent based segmentation: Application to MRI brain scans LOCUS: LOcal Cooperative Unified Segmentation of MRI brain scans, Proceedings of the 11th conference on artificial intelligence in medicine Proceedings of the 10th international conference on medical image computing and computer assisted intervention, pp.2007-219, 2007.

K. Held, E. Kopps, B. Krause, W. Wells, R. Kikinis et al., Markov random field segmentation of brain MR images, IEEE Transactions on Medical Imaging, vol.16, issue.6, pp.878-86, 1997.
DOI : 10.1109/42.650883

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, vol.18, issue.10, pp.897-908, 1999.
DOI : 10.1109/42.811270

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, vol.20, issue.1, pp.45-52, 2001.
DOI : 10.1109/42.906424

V. Barra and J. Boire, Automatic segmentation of subcortical brain structures in MR images using information fusion, IEEE Transactions on Medical Imaging, vol.20, issue.7, pp.549-58, 2001.
DOI : 10.1109/42.932740

O. Colliot, O. Camara, and I. Bloch, Integration of fuzzy spatial relations in deformable models???Application to brain MRI segmentation, Pattern Recognition, vol.39, issue.8, pp.1401-1415, 2006.
DOI : 10.1016/j.patcog.2006.02.022
URL : https://hal.archives-ouvertes.fr/hal-00878443

D. Collins, A. Zijdenbos, V. Kollokian, J. Sled, N. Kabani et al., Design and construction of a realistic digital brain phantom, IEEE Transactions on Medical Imaging, vol.17, issue.3, pp.463-471, 1998.
DOI : 10.1109/42.712135

R. Nowak, Distributed EM algorithms for density estimation and clustering in sensor networks, IEEE Transactions on Signal Processing, vol.51, issue.8, pp.2245-53, 2003.
DOI : 10.1109/TSP.2003.814623

T. Mensink, W. Zajdel, and B. Krose, Distributed EM Learning for Appearance Based Multi-Camera Tracking, 2007 First ACM/IEEE International Conference on Distributed Smart Cameras, pp.178-85, 2007.
DOI : 10.1109/ICDSC.2007.4357522
URL : https://hal.archives-ouvertes.fr/inria-00548678