W. Longstreth, T. Manolio, A. Arnold, G. Burke, and N. Bryan, Clinical Correlates of White Matter Findings on Cranial Magnetic Resonance Imaging of 3301 Elderly People: The Cardiovascular Health Study, Stroke, vol.27, issue.8, pp.1274-1282, 1996.
DOI : 10.1161/01.STR.27.8.1274

M. Vernooij, M. Ikram, H. Tanghe, A. Vincent, and A. Hofman, Incidental Findings on Brain MRI in the General Population, New England Journal of Medicine, vol.357, issue.18, pp.1821-1828, 2007.
DOI : 10.1056/NEJMoa070972

L. Kuller, W. Longstreth, . Jr, A. Arnold, C. Bernick et al., White Matter Hyperintensity on Cranial Magnetic Resonance Imaging: A Predictor of Stroke, Stroke, vol.35, issue.8, pp.1821-1825, 2004.
DOI : 10.1161/01.STR.0000132193.35955.69

L. Herrmann, L. Masurier, M. Ebmeier, and K. , White matter hyperintensities in late life depression: a systematic review, Journal of Neurology, Neurosurgery & Psychiatry, vol.79, issue.6, pp.619-624, 2008.
DOI : 10.1136/jnnp.2007.124651

N. Hirono, H. Kitagaki, H. Kazui, M. Hashimoto, and E. Mori, Impact of White Matter Changes on Clinical Manifestation of Alzheimer's Disease : A Quantitative Study, Stroke, vol.31, issue.9, pp.2182-2188, 2000.
DOI : 10.1161/01.STR.31.9.2182

C. Guttmann, R. Benson, S. Warfield, X. Wei, and M. Anderson, White matter abnormalities in mobility-impaired older persons, Neurology, vol.54, issue.6, pp.1277-1283, 2000.
DOI : 10.1212/WNL.54.6.1277

URL : http://spl.bwh.harvard.edu:8000/~warfield/./papers/2000/guttmann-wma.pdf

R. Au, J. Massaro, P. Wolf, M. Young, and A. Beiser, Association of White Matter Hyperintensity Volume With Decreased Cognitive Functioning, Archives of Neurology, vol.63, issue.2, 2006.
DOI : 10.1001/archneur.63.2.246

M. Ikram, H. Vrooman, M. Vernooij, T. Den-heijer, and A. Hofman, Brain tissue volumes in relation to cognitive function and risk of dementia, Neurobiology of Aging, vol.31, issue.3, pp.378-386, 2010.
DOI : 10.1016/j.neurobiolaging.2008.04.008

S. Debette and H. Markus, The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis, BMJ, vol.341, issue.jul26 1, p.3666, 2010.
DOI : 10.1136/bmj.c3666

F. Fazekas, R. Kleinert, H. Offenbacher, R. Schmidt, and G. Kleinert, Pathologic correlates of incidental MRI white matter signal hyperintensities, Neurology, vol.43, issue.9, pp.1683-1689, 1993.
DOI : 10.1212/WNL.43.9.1683

A. Joutel, C. Corpechot, A. Ducros, K. Vahedi, and H. Chabriat, Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia, Nature, vol.383, issue.6602, pp.707-710, 1996.
DOI : 10.1038/383707a0

H. Chabriat, A. Joutel, M. Dichgans, E. Tournier-lasserve, and M. Bousser, CADASIL, The Lancet Neurology, vol.8, issue.7, pp.643-653, 2009.
DOI : 10.1016/S1474-4422(09)70127-9

URL : https://hal.archives-ouvertes.fr/hal-00349728

R. Mä-ntylä, T. Erkinjuntti, O. Salonen, H. Aronen, and T. Peltonen, Variable Agreement Between Visual Rating Scales for White Matter Hyperintensities on MRI : Comparison of 13 Rating Scales in a Poststroke Cohort, Stroke, vol.28, issue.8, pp.1614-1623, 1997.
DOI : 10.1161/01.STR.28.8.1614

A. Brickman, J. Sneed, F. Provenzano, E. Garcon, and L. Johnert, Quantitative approaches for assessment of white matter hyperintensities in elderly populations Measuring Longitudinal White Matter Changes: Comparison of a Visual Rating Scale with a Volumetric Measurement, Psychiatry Res American Journal of Neuroradiology, vol.193, issue.27, pp.101-106, 2006.

M. Duering, N. Zieren, D. Hervé, E. Jouvent, and S. Reyes, Strategic role of frontal white matter tracts in vascular cognitive impairment: a voxel-based lesion-symptom mapping study in CADASIL Available:http://brain. oxfordjournals.org/content, Brain, 2011.

C. Jack, O. Jr, P. Brien, D. Rettman, M. Shiung et al., FLAIR histogram segmentation for measurement of leukoaraiosis volume, Journal of Magnetic Resonance Imaging, vol.16, issue.6, pp.668-676, 2001.
DOI : 10.1109/42.640750

W. Wen and P. Sachdev, The topography of white matter hyperintensities on brain MRI in healthy 60- to 64-year-old individuals, NeuroImage, vol.22, issue.1, pp.144-154, 2004.
DOI : 10.1016/j.neuroimage.2003.12.027

F. Admiraal-behloul, D. Van-den-heuvel, H. Olofsen, M. Van-osch, and J. Van-der-grond, Fully automatic segmentation of white matter hyperintensities in MR images of the elderly, NeuroImage, vol.28, issue.3, pp.607-617, 2005.
DOI : 10.1016/j.neuroimage.2005.06.061

E. Gibson, F. Gao, S. Black, and N. Lobaugh, Automatic segmentation of white matter hyperintensities in the elderly using FLAIR images at 3T, Journal of Magnetic Resonance Imaging, vol.22, issue.6, pp.1311-1322, 2010.
DOI : 10.2214/ajr.176.5.1761313

P. Maillard, N. Delcroix, F. Crivello, C. Dufouil, and S. Gicquel, An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre reproducibility based on two large community databases, Neuroradiology, vol.27, issue.Suppl 3, pp.31-42, 2007.
DOI : 10.2214/ajr.181.2.1810571

URL : https://hal.archives-ouvertes.fr/inserm-00180711

E. Smith, D. Salat, J. Jeng, C. Mccreary, and B. Fischl, Correlations between MRI white matter lesion location and executive function and episodic memory, Neurology, vol.76, issue.17, pp.1492-1499, 2011.
DOI : 10.1212/WNL.0b013e318217e7c8

URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3087468/pdf

P. Anbeek, K. Vincken, M. Van-osch, R. Bisschops, and J. Van-der-grond, Probabilistic segmentation of white matter lesions in MR imaging, NeuroImage, vol.21, issue.3, pp.1037-1044, 2004.
DOI : 10.1016/j.neuroimage.2003.10.012

R. De-boer, H. Vrooman, F. Van-der-lijn, M. Vernooij, and M. Ikram, White matter lesion extension to automatic brain tissue segmentation on MRI, NeuroImage, vol.45, issue.4, pp.1151-1161, 2009.
DOI : 10.1016/j.neuroimage.2009.01.011

Z. Lao, D. Shen, D. Liu, A. Jawad, and E. Melhem, Computer-Assisted Segmentation of White Matter Lesions in 3D MR Images Using Support Vector Machine, Academic Radiology, vol.15, issue.3, pp.300-313, 2008.
DOI : 10.1016/j.acra.2007.10.012

S. Klöppel, A. Abdulkadir, S. Hadjidemetriou, S. Issleib, and L. Frings, A comparison of different automated methods for the detection of white matter lesions in MRI data, NeuroImage, vol.57, issue.2, pp.416-422, 2011.
DOI : 10.1016/j.neuroimage.2011.04.053

N. Otsu, A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.62-66, 1979.
DOI : 10.1109/TSMC.1979.4310076

J. Ashburner and K. Friston, Unified segmentation, NeuroImage, vol.26, issue.3, pp.839-851, 2005.
DOI : 10.1016/j.neuroimage.2005.02.018

P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.12, issue.7, pp.629-639, 1990.
DOI : 10.1109/34.56205

URL : http://www.cs.huji.ac.il/~cheny/reading/diffusion/classic.pdf

M. Black, G. Sapiro, D. Marimont, and D. Heeger, Robust anisotropic diffusion, IEEE Transactions on Image Processing, vol.7, issue.3, pp.421-432, 1998.
DOI : 10.1109/83.661192

B. Dubois, M. Sarazin, S. Lehéricy, M. Chupin, and L. Garnero, Effects of Donepezil on structural MRI and clinical markers in patients with amnesic mild cognitive impairment: a randomized, 2009.

J. Bland and D. Altman, Statistical methods for assessing agreement between two methods of clinical measurement, International Journal of Nursing Studies, vol.47, issue.8, pp.307-310, 1986.
DOI : 10.1016/j.ijnurstu.2009.10.001

J. Bland and D. Altman, Measuring agreement in method comparison studies, Statistical Methods in Medical Research, vol.315, issue.2, pp.135-160, 1999.
DOI : 10.1056/NEJM198607313150503

L. Dice, Measures of the Amount of Ecologic Association Between Species, Ecology, vol.26, issue.3, pp.297-302, 1945.
DOI : 10.2307/1932409

S. Durgerian, M. Lancaster, M. Seidenberg, K. Nielson, and J. Woodard, White matter diffusivity is higher among healthy elders at increased risk for Alzheimer's disease, 2011.

A. Dale, B. Fischl, and M. Sereno, Cortical Surface-Based Analysis, NeuroImage, vol.9, issue.2, pp.179-194, 1999.
DOI : 10.1006/nimg.1998.0395

B. Fischl, M. Sereno, and A. Dale, Cortical Surface-Based Analysis, NeuroImage, vol.9, issue.2, pp.195-207, 1998.
DOI : 10.1006/nimg.1998.0396

B. Fischl, D. Salat, E. Busa, M. Albert, and M. Dieterich, Whole Brain Segmentation, Neuron, vol.33, issue.3, pp.341-355, 2002.
DOI : 10.1016/S0896-6273(02)00569-X

B. Fischl, D. Salat, A. Van-der-kouwe, N. Makris, and F. Ségonne, Sequence-independent segmentation of magnetic resonance images, NeuroImage, vol.23, issue.1, 2004.
DOI : 10.1016/j.neuroimage.2004.07.016

URL : http://www.nmr.mgh.harvard.edu/~fischl/reprints/sequence_independent_segmentation_reprint.pdf

F. Ségonne, J. Pacheco, and B. Fischl, Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops, IEEE Transactions on Medical Imaging, vol.26, issue.4, pp.518-529, 2007.
DOI : 10.1109/TMI.2006.887364

M. Wu, C. Rosano, M. Butters, E. Whyte, and M. Nable, A fully automated method for quantifying and localizing white matter hyperintensities on MR images, Psychiatry Research: Neuroimaging, vol.148, issue.2-3, pp.133-142, 2006.
DOI : 10.1016/j.pscychresns.2006.09.003

URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1761950/pdf

V. Vapnik, P. Raniga, P. Schmitt, P. Bourgeat, J. Fripp et al., The nature of statistical learning theory 188 p. 43 Local intensity model: An outlier detection framework with applications to white matter hyperintensity segmentation, IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE, pp.2057-2060, 1995.

C. Eckerström, E. Olsson, N. Klasson, M. Bjerke, and M. Göthlin, High White Matter Lesion Load Is Associated with Hippocampal Atrophy in Mild Cognitive Impairment, Dementia and Geriatric Cognitive Disorders, vol.31, issue.2, pp.132-138, 2011.
DOI : 10.1159/000323014

A. Zijdenbos, R. Forghani, and A. Evans, Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis, IEEE Transactions on Medical Imaging, vol.21, issue.10, pp.1280-1291, 2002.
DOI : 10.1109/TMI.2002.806283

T. Dyrby, E. Rostrup, W. Baaré, E. Van-straaten, and F. Barkhof, Segmentation of age-related white matter changes in a clinical multi-center study, NeuroImage, vol.41, issue.2, pp.335-345, 2008.
DOI : 10.1016/j.neuroimage.2008.02.024