Longitudinal change detection: inference on the diffusion tensor along white matter pathways.

Date publication

avril 2013

Journal

Medical image analysis

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, Kremer S, Armspach JP

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/23453084

Résumé

Diffusion weighted magnetic resonance imaging (DW-MRI) makes it possible 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 local or global fiber diffusion property modifications between two longitudinal DW-MRI acquisitions of a patient. To this end, we develop two frameworks based on statistical tests on tensor eigenvalues to detect local or global changes along the white matter pathways: a pointwise test that compares tensor populations extracted in bundles cross sections and a fiberwise test that compares paired tensors along all the fiber bundles. Experiments on both synthetic and real data highlight the benefit of considering fiber based statistical tests compared to standard voxelwise strategies.

Mots clés

Algorithms, Diffusion Tensor Imaging, methods, Humans, Image Enhancement, methods, Image Interpretation, Computer-Assisted, methods, Imaging, Three-Dimensional, methods, Longitudinal Studies, Nerve Fibers, Myelinated, pathology, Neural Pathways, pathology, Neuromyelitis Optica, pathology, Optic Nerve, pathology, Pattern Recognition, Automated, methods, Reproducibility of Results, Sensitivity and Specificity

Référence

Med Image Anal. 2013 Apr;17(3):375-86