The variational Bayesian EM Algorithm for incomplete data: with application to scoring graphical model structures. Bayesian Statistics, 2003. ,
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
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
An Optimized Blockwise Non Local Means Denoising (a) (b) (c) ,
Real MS data, patient 3. (a): Flair image. (b): identified lesions with our approach (DSC 45%). (c): ground truth ,
Measures of the Amount of Ecologic Association Between Species, Ecology, vol.26, issue.3, pp.297-302, 1945. ,
DOI : 10.2307/1932409
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
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
Entropy minimization for automatic correction of intensity nonuniformity, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. MMBIA-2000 (Cat. No.PR00737), p.162, 2000. ,
DOI : 10.1109/MMBIA.2000.852374
Finite Mixture Models, 2000. ,
DOI : 10.1002/0471721182
An a contrario approach for outliers segmentation: Application to Multiple Sclerosis in MRI, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.9-12, 2008. ,
DOI : 10.1109/ISBI.2008.4540919
Unified Approach for Multiple Sclerosis Lesion Segmentation on Brain MRI, Annals of Biomedical Engineering, vol.21, issue.1, pp.142-151, 2006. ,
DOI : 10.1007/s10439-005-9009-0
Fully Bayesian Joint Model for MR Brain Scan Tissue and Structure Segmentation, MICCAI, pp.1066-1074, 2008. ,
DOI : 10.1007/978-3-540-85990-1_128
URL : https://hal.archives-ouvertes.fr/inserm-00356883
Lesion identification using unified segmentation-normalisation models and fuzzy clustering, NeuroImage, vol.41, issue.4, pp.1253-1266, 2008. ,
DOI : 10.1016/j.neuroimage.2008.03.028
URL : http://doi.org/10.1016/j.neuroimage.2008.03.028
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