C. Barillot, G. Edan, and O. Commowick, Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging, Medical Image Analysis, vol.33, pp.134-139, 2016.
DOI : 10.1016/j.media.2016.06.017

URL : https://hal.archives-ouvertes.fr/hal-01333583

H. Lassmann, W. Brück, and C. Lucchinetti, Heterogeneity of multiple sclerosis pathogenesis: implications for diagnosis and therapy, Trends in Molecular Medicine, vol.7, issue.3, pp.115-121, 2001.
DOI : 10.1016/S1471-4914(00)01909-2

A. Mackay, C. Laule, I. Vavasour, T. Bjarnason, S. Kolind et al., Insights into brain microstructure from the T2 distribution, Magnetic Resonance Imaging, vol.24, issue.4, pp.515-525, 2006.
DOI : 10.1016/j.mri.2005.12.037

K. P. Whittall, A. L. Mackay, D. A. Graeb, R. A. Nugent, K. David et al., In vivo measurement ofT2 distributions and water contents in normal human brain, Magnetic Resonance in Medicine, vol.94, issue.1, pp.34-43, 1997.
DOI : 10.1007/978-1-4757-1830-0_5

C. Laule, E. Leung, D. Li, A. L. Traboulsee, D. W. Paty et al., Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology, Multiple Sclerosis Journal, vol.139, issue.6, pp.747-753, 2006.
DOI : 10.1016/0730-725X(95)00007-4

A. L. Mackay and C. Laule, Magnetic Resonance of Myelin Water: An??in vivo Marker for Myelin, Brain Plasticity, vol.8, issue.32, pp.71-91, 2016.
DOI : 10.3389/fnhum.2014.00671

A. Akhondi?asl, O. Afacan, M. Balasubramanian, R. V. Mulkern, and S. K. Warfield, Fast myelin water fraction estimation using 2D multislice CPMG, Magnetic Resonance in Medicine, vol.73, issue.4, pp.1301-1313, 2016.
DOI : 10.1002/mrm.25108

S. Chatterjee, O. Commowick, S. Warfield, and C. Barillot, Gaining Insights Into Multiple Sclerosis Lesion Characteristics from Brain Tissue Microstructure Information: A Multi- Compartment T2 Relaxometry Approach, ISMRM 25TH ANNUAL MEETING & EXHIBITION, 2017.
URL : https://hal.archives-ouvertes.fr/inserm-01543061

T. Prasloski, B. Mädler, Q. Xiang, A. Mackay, and C. Jones, Applications of stimulated echo correction to multicomponent T2 analysis, Magnetic Resonance in Medicine, vol.34, issue.6, pp.1803-1814, 2012.
DOI : 10.1063/1.1731821

J. L. Lancaster, T. Andrews, L. J. Hardies, S. Dodd, and P. T. Fox, Three-pool model of white matter, Journal of Magnetic Resonance Imaging, vol.4, issue.1, pp.1-10, 2003.
DOI : 10.1093/cercor/4.4.331

URL : http://onlinelibrary.wiley.com/doi/10.1002/jmri.10230/pdf

O. Commowick, N. Wiest-daesslé, and S. Prima, Block-matching strategies for rigid registration of multimodal medical images, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.700-703, 2012.
DOI : 10.1109/ISBI.2012.6235644

URL : https://hal.archives-ouvertes.fr/inserm-00681610

S. Ourselin, A. Roche, S. Prima, and N. Ayache, Block Matching: A??General??Framework??to??Improve Robustness of??Rigid??Registration of Medical Images, In MICCAI, vol.1935, pp.557-566, 2000.
DOI : 10.1007/978-3-540-40899-4_57

URL : https://hal.archives-ouvertes.fr/inria-00615860

W. S. Vargas, E. Monohan, S. Pandya, A. Raj, T. Vartanian et al., Measuring longitudinal myelin water fraction in new multiple sclerosis lesions, NeuroImage: Clinical, vol.9, pp.369-375, 2015.
DOI : 10.1016/j.nicl.2015.09.003

URL : https://doi.org/10.1016/j.nicl.2015.09.003

A. Kerbrat, B. Combès, O. Commowick, A. Maarouf, E. Bannier et al., USPIO-positive MS lesions are associated with greater tissue damage than gadolinium-positive-only lesions during 3-year followup, Multiple Sclerosis Journal, p.1352458517736148, 2017.
DOI : 10.1177/1352458517736148

URL : https://hal.archives-ouvertes.fr/hal-01647039