Longitudinal change detection: inference on the diffusion tensor along white-matter pathways.
Fiche publication
Date publication
janvier 2011
Journal
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Auteurs
Membres identifiés du Cancéropôle Est :
Pr HEITZ Fabrice, Pr DE SEZE Jérôme, Dr NOBLET Vincent
Tous les auteurs :
Grigis A, Noblet V, Blanc F, Heitz F, de Seze J, Armspach JP
Lien Pubmed
Résumé
Diffusion tensor magnetic resonance imaging (DT-MRI) tractography allows to probe brain connections in vivo. This paper presents a change detection framework that relies on white-matter pathways with application to neuromyelitis optica (NMO). The objective is to detect global or local fiber diffusion property modifications between two longitudinal DT-MRI acquisitions of a patient. To this end, estimation and testing tools on tensors along the white-matter pathways are considered. Two tests are implemented: a pointwise test that compares at each sampling point of the fiber bundle the tensor populations of the two exams in the cross section of the bundle and a fiberwise test that compares paired tensors along all the fiber bundle. Experiments on both synthetic and real data highlight the benefit of considering fiber based statistical tests compared to the standard voxelwise strategy.
Mots clés
Algorithms, Brain, pathology, Cluster Analysis, Computer Simulation, Diffusion Magnetic Resonance Imaging, methods, Diffusion Tensor Imaging, methods, Humans, Image Processing, Computer-Assisted, Models, Statistical, Multivariate Analysis, Nerve Fibers, Myelinated, pathology, Nerve Tissue, pathology, Neuromyelitis Optica, pathology
Référence
Med Image Comput Comput Assist Interv. 2011 ;14(Pt 2):1-8