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T-distributed stochastic neighbor embedding clustering for all segmentations: these figures demonstrate strong clustering of the data under a T-SNE algorithm, and this allows apparently perfectly discrimination between lesions and non-lesions with T1 (a) T2 (b) and combining the two properties (c) features. NAWM: frontal normal appearing white matter; MS: Multiple Sclerosis. The data depicted in circles refers to patients with MS and the data on square to controls
