Multi-Parametric Non-Negative Matrix Factorization for Longitudinal Variations Detection in White Matter Fiber-Bundles

Claudio Stamile (1) , Gabriel Kocevar (1) , Francois Cotton (1, 2) , Frederik Maes (3) , Dominique Sappey-Marinier (1, 4) , Sabine van Huffel (3)

1 RMN et optique : De la mesure au biomarqueur
2 Département de Neuroradiologie [Centre Hospitalier Lyon Sud - HCL]
3 KU Leuven - Catholic University of Leuven = Katholieke Universiteit Leuven
4 CERMEP - imagerie du vivant - Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant

Processing of longitudinal diffusion tensor imaging (DTI) data is a crucial challenge to better understand pathological mechanisms of complex brain diseases such as multiple sclerosis (MS) where white matter (WM) fiber-bundles are variably altered by inflammatory events.

Domaines: Imagerie

Claudio Stamile, Gabriel Kocevar, Francois Cotton, Frederik Maes, Dominique Sappey-Marinier, et al.. Multi-Parametric Non-Negative Matrix Factorization for Longitudinal Variations Detection in White Matter Fiber-Bundles. IEEE Journal of Biomedical and Health Informatics, 2017, 21 (5), pp.1393-1402. ⟨10.1109/JBHI.2016.2597963⟩. ⟨hal-01492687⟩