A. Sorensen, O. Wu, W. Copen, T. Davis, R. Gonzalez et al., Human Acute Cerebral Ischemia: Detection of Changes in Water Diffusion Anisotropy by Using MR Imaging, Radiology, vol.212, issue.3, pp.785-792, 1999.
DOI : 10.1148/radiology.212.3.r99se24785

J. Manjon, P. Coupe, C. L. Buades, A. Collins, D. Robles et al., Diffusion Weighted Image Denoising Using Overcomplete Local PCA, PLoS ONE, vol.103, issue.1, p.73021, 2013.
DOI : 10.1371/journal.pone.0073021.g009

URL : https://hal.archives-ouvertes.fr/hal-00871777

B. Avants, N. Tustison, G. Song, P. Cook, A. Klein et al., A reproducible evaluation of ANTs similarity metric performance in brain image registration, NeuroImage, vol.54, issue.3, pp.2033-2044, 2011.
DOI : 10.1016/j.neuroimage.2010.09.025

S. Wakana, H. Jiang, L. Nagae-­?poetscher, P. Van-zijl, and S. Mori, Fiber Tract???based Atlas of Human White Matter Anatomy, Radiology, vol.230, issue.1, pp.77-87, 2004.
DOI : 10.1148/radiol.2301021640

J. Sanford, J. Moreland, L. Swanson, P. Stratford, and C. Gowland, Reliability of the Fugl-Meyer Assessment for Testing Motor Performance in Patients Following Stroke, Physical Therapy, vol.73, issue.7, pp.447-454, 1993.
DOI : 10.1093/ptj/73.7.447

M. Kuhn, D. Mikulis, D. Ayoub, B. Kosofsky, K. Davis et al., Wallerian degeneration after cerebral infarction: evaluation with sequential MR imaging., Radiology, vol.172, issue.1, pp.179-182, 1989.
DOI : 10.1148/radiology.172.1.2740501

G. Thomalla, V. Glauche, C. Weiller, and J. Rother, Time course of wallerian degeneration after ischaemic stroke revealed by diffusion tensor imaging, Journal of Neurology, Neurosurgery & Psychiatry, vol.76, issue.2, pp.266-268, 2005.
DOI : 10.1136/jnnp.2004.046375

H. Iizuka, K. Sakatani, and W. Young, Corticofugal axonal degeneration in rats after middle cerebral artery occlusion, Stroke, vol.20, issue.10, pp.1396-1402, 1989.
DOI : 10.1161/01.STR.20.10.1396

Y. Bhagat, M. Hussain, R. Stobbe, K. Butcher, D. Emery et al., Elevations of diffusion anisotropy are associated with hyper-­?acute stroke: A serial imaging study Lesion load of the corticospinal tract predicts motor impairment in chronic stroke, Magn Reson Imaging. Stroke, vol.2641, pp.683-693, 2008.

M. Lansberg, O. Brien, M. Tong, D. Moseley, M. Albers et al., Evolution of Cerebral Infarct Volume Assessed by Diffusion-Weighted Magnetic Resonance Imaging, Archives of Neurology, vol.58, issue.4, pp.613-617, 2001.
DOI : 10.1001/archneur.58.4.613

J. Krakauer and R. Marshall, The proportional recovery rule for stroke revisited. [Published online ahead of print, Ann Neurol, 2015.

C. Stinear, P. Barber, M. Petoe, S. Anwar, and W. Byblow, The PREP algorithm predicts potential for upper limb recovery after stroke, Brain, vol.135, issue.8, pp.2527-2535, 2012.
DOI : 10.1093/brain/aws146

J. Green, Brain Reorganization After Stroke, Topics in Stroke Rehabilitation, vol.22, issue.1, pp.1-20, 2003.
DOI : 10.1161/01.STR.30.12.2659

S. Zeiler and J. Krakauer, The interaction between training and plasticity in the poststroke brain, Current Opinion in Neurology, vol.26, issue.6, pp.609-616, 2013.
DOI : 10.1097/WCO.0000000000000025

R. Marshall, E. Zarahn, L. Alon, B. Minzer, R. Lazar et al., Early imaging correlates of subsequent motor recovery after stroke, Annals of Neurology, vol.25, issue.5
DOI : 10.1002/ana.21636

E. Zarahn, L. Alon, S. Ryan, R. Lazar, M. Vry et al., Prediction of Motor Recovery Using Initial Impairment and fMRI 48 h Poststroke, Cerebral Cortex, vol.21, issue.12, pp.2712-2721, 2011.
DOI : 10.1093/cercor/bhr047

D. Lee, J. Park, S. Park, and C. Hong, Have You Ever Seen the Impact of Crossing Fiber in DTI?: Demonstration of the Corticospinal Tract Pathway, PLOS ONE, vol.28, issue.7, p.112045, 2015.
DOI : 10.1371/journal.pone.0112045.g002