title: Longitudinal change detection: inference on the diffusion tensor along white matter pathways.
abstract: 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.
authors: University of Strasbourg, CNRS, ICube, FMTS Strasbourg, France. grigis@unistra.fr
authors: Antoine
authors: A
authors: Grigis
authors: Vincent
authors: V
authors: Noblet
authors: Fréderic
authors: F
authors: Blanc
authors: Fabrice
authors: F
authors: Heitz
authors: Jérome
authors: J
authors: de Seze
authors: Stéphane
authors: S
authors: Kremer
authors: Jean-Paul
authors: JP
authors: Armspach
mesh_terms: D000465:Algorithms; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008137:Longitudinal Studies; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D009434:Neural Pathways / Q000473:pathology; D009471:Neuromyelitis Optica / Q000473:pathology*; D009900:Optic Nerve / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity