D. Garcia-lorenzo, S. Francis, S. Narayanan, D. L. Arnold, and D. L. Collins, Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging, Med Image Anal, vol.17, issue.1, pp.1-18, 2013.

C. H. Polman, Diagnostic criteria for multiple sclerosis: 2005 revisions to the Mc Donald criteria, Ann Neurol, vol.58, pp.840-846, 2005.

A. Robin, L. Moisan, L. Hgarat-mascle, and S. , An a-contrario approach for sub-pixel change detection in satellite imagery, IEEE Trans Pattern Anal Mach Intell, vol.32, pp.1977-93, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00399698

C. Maumet, P. Maurel, J. C. Ferré, and C. Barillot, An a contrario approach for the detection of patient-specific brain perfusion abnormalities with arterial spin labelling, NeuroImage, vol.134, pp.424-433, 2016.
URL : https://hal.archives-ouvertes.fr/inserm-01291748

F. Rousseau, S. Faisan, F. Heitz, J. P. Armspach, Y. Chevalier et al., An a contrario approach for change detection in 3D multimodal images: application to multiple sclerosis in MRI, IEEE International Symposium on Biomedical Imaging (ISBI), pp.2069-2072, 2007.

O. Commowick, A. Maarouf, J. C. Ferré, J. P. Ranjeva, G. Edan et al., Diffusion MRI abnormalities detection with orientation distribution functions: a multiple sclerosis longitudinal study, Med Image Anal, vol.22, pp.114-137, 2015.
URL : https://hal.archives-ouvertes.fr/inserm-01134107

N. Otsu, A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, pp.62-66, 1979.

R. E. Gabr, K. M. Hasan, M. E. Haque, F. M. Nelson, J. S. Wolinsky et al., Optimal combination of FLAIR and T2weighted MRI for improved lesion contrast in multiple sclerosis, J. Magn. Reson. Imaging, vol.44, pp.1293-1300, 2016.

O. Commowick, Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure, bioRxiv, vol.367557, 2018.
URL : https://hal.archives-ouvertes.fr/inserm-01895603

A. Akhondi-asl, L. Hoyte, M. E. Lockhart, and S. K. Warfield, A Logarithmic Opinion Pool Based STAPLE Algorithm For The Fusion of Segmentations With Associated Reliability Weights, IEEE Trans. Med. Imaging, vol.33, 1997.

P. Coupe, An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images, IEEE Trans. Med. Imaging, vol.27, pp.425-466, 2008.
URL : https://hal.archives-ouvertes.fr/inserm-00169658

O. Commowick, N. Wiest-daesslé, and S. Prima, Block matching strategies for rigid registration of multimodal medical images, IEEE International Symposium on Biomedical Imaging (ISBI), pp.700-703, 2012.
URL : https://hal.archives-ouvertes.fr/inserm-00681610

J. V. Manjn and P. Coup, An Online MRI Brain Volumetry System, Front. Neuroinformatics, vol.10, 2016.

N. J. Tustison, N4ITK: improved N3 bias correction, IEEE Trans. Med. Imaging, vol.29, pp.1310-1320, 2010.

A. Guimond, J. Meunier, and J. P. Thirion, Average Brain Models, Comput Vis Image Underst, vol.77, pp.192-210, 2000.
URL : https://hal.archives-ouvertes.fr/inria-00072934

O. Commowick, N. Wiest-daesslé, and S. Prima, Automated diffeomorphic registration of anatomical structures with rigid parts: application to dynamic cervical MRI, MICCAI, vol.15, pp.163-170, 2012.
URL : https://hal.archives-ouvertes.fr/inserm-00716106

D. Virmani, S. Taneja, and G. Malhotra, Normalization based K means Clustering Algorithm, 2015.

Y. Hochberg and A. Tamhane, Multiple Comparison Procedures, 1987.