title: Spatial regularization of SVM for the detection of diffusion alterations associated with stroke outcome.
abstract: In this paper, we propose a new method to detect differences at the group level in brain images based on spatially regularized support vector machines (SVM). We propose to spatially regularize the SVM using a graph Laplacian. This provides a flexible approach to model different types of proximity between voxels. We propose a proximity graph which accounts for tissue types. An efficient computation of the Gram matrix is provided. Then, significant differences between two populations are detected using statistical tests on the outputs of the SVM. The method was first tested on synthetic examples. It was then applied to 72 stroke patients to detect brain areas associated with motor outcome at 90 days, based on diffusion-weighted images acquired at the acute stage (median delay one day). The proposed method showed that poor motor outcome is associated to changes in the corticospinal bundle and white matter tracts originating from the premotor cortex. Standard mass univariate analyses failed to detect any difference on the same population.
authors.affiliation: UPMC Université Paris 6, UMR 7225, UMR_S 975, Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Paris F-75013, France. remi.cuingnet@imed.jussieu.fr
authors.forename: Rémi
authors.initials: R
authors.lastname: Cuingnet
authors.forename: Charlotte
authors.initials: C
authors.lastname: Rosso
authors.forename: Marie
authors.initials: M
authors.lastname: Chupin
authors.forename: Stéphane
authors.initials: S
authors.lastname: Lehéricy
authors.forename: Didier
authors.initials: D
authors.lastname: Dormont
authors.forename: Habib
authors.initials: H
authors.lastname: Benali
authors.forename: Yves
authors.initials: Y
authors.lastname: Samson
authors.forename: Olivier
authors.initials: O
authors.lastname: Colliot
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009044:Motor Cortex / Q000473:pathology*; D017063:Outcome Assessment, Health Care; D010363:Pattern Recognition, Automated / Q000379:methods; D011379:Prognosis; D020521:Stroke / Q000473:pathology*