We propose a novel automatic WMH segmentation method based on a convolutional neural network to study the longitudinal WMH changes among a cohort of 101 CADASIL patients. We demonstrate that this method is able to produce consistent quantitative measures of WMH volume by the strong correlation between the computed baseline WMH volume and the clinically assessed Fazekas score. Our main results show that the progression of WMH is correlated to the baseline volume and that this progression largely vary at individual level although a rapid extension is mainly detected between 40 and 60 years in the whole population.
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