A. Compston and A. Coles, Multiple sclerosis, The Lancet, vol.372, issue.9648, pp.1502-1517, 2008.
DOI : 10.1016/S0140-6736(08)61620-7

URL : https://hal.archives-ouvertes.fr/hal-00996686

D. W. Paty, J. J. Oger, L. F. Kastrukoff, S. A. Hashimoto, J. P. Hooge et al., MRI in the diagnosis of MS: A prospective study with comparison of clinical evaluation, evoked potentials, oligoclonal banding, and CT, Neurology, vol.38, issue.2, pp.38180-185, 1988.
DOI : 10.1212/WNL.38.2.180

F. Barkhof, M. Filippi, D. H. Miller, P. Scheltens, A. Campi et al., Comparison of MRI criteria at first presentation to predict conversion to clinically definite multiple sclerosis, Brain, vol.120, issue.11, pp.1202059-2069, 1997.
DOI : 10.1093/brain/120.11.2059

J. H. Woo, L. P. Henry, J. Krejza, and E. R. Melhem, Detection of Simulated Multiple Sclerosis Lesions on T2-weighted and FLAIR Images of the Brain: Observer Performance, Radiology, vol.241, issue.1, pp.206-212, 2006.
DOI : 10.1148/radiol.2411050792

J. Eugenio-iglesias, E. Konukoglu, D. Zikic, B. Glocker, K. Van-leemput et al., Is synthesizing mri contrast useful for intermodality analysis? In Medical Image Computing and Computer-Assisted Intervention ? MICCAI 2013, Lecture Notes in Computer Science, vol.8149

G. Van-tulder and M. De-bruijne, Why does synthesized data improve multisequence classification? In Medical Image Computing and Computer-Assisted Intervention ? MICCAI 2015, Lecture Notes in Computer Science, vol.9349

D. Dong-hye-ye, B. Zikic, A. Glocker, E. Criminisi, and . Konukoglu, Modality propagation: Coherent synthesis of subject-specific scans with data-driven regularization, Medical Image Computing and Computer-Assisted Intervention ? MICCAI 2013

A. Jog, A. Carass, D. L. Pham, and J. L. Prince, Random Forest FLAIR Reconstruction from T1, T2, and PD -Weighted MRI, Proc IEEE Int Symp Biomed Imaging, vol.2014, pp.1079-1082, 2014.