Representing diffusion MRI in 5-D simplifies regularization and segmentation of white matter tracts.

Détails

ID Serval
serval:BIB_7E6AB4F67C24
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Representing diffusion MRI in 5-D simplifies regularization and segmentation of white matter tracts.
Périodique
IEEE Transactions on Medical Imaging
Auteur(s)
Jonasson L., Bresson X., Thiran J.P., Wedeen V.J., Hagmann P.
ISSN
0278-0062
Statut éditorial
Publié
Date de publication
11/2007
Peer-reviewed
Oui
Volume
26
Numéro
11
Pages
1547-1554
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't Publication Status: ppublish
Résumé
We present a new five-dimensional (5-D) space representation of diffusion magnetic resonance imaging (dMRI) of high angular resolution. This 5-D space is basically a non-Euclidean space of position and orientation in which crossing fiber tracts can be clearly disentangled, that cannot be separated in three-dimensional position space. This new representation provides many possibilities for processing and analysis since classical methods for scalar images can be extended to higher dimensions even if the spaces are not Euclidean. In this paper, we show examples of how regularization and segmentation of dMRI is simplified with this new representation. The regularization is used with the purpose of denoising and but also to facilitate the segmentation task by using several scales, each scale representing a different level of resolution. We implement in five dimensions the Chan-Vese method combined with active contours without edges for the segmentation and the total variation functional for the regularization. The purpose of this paper is to explore the possibility of segmenting white matter structures directly as entirely separated bundles in this 5-D space. We will present results from a synthetic model and results on real data of a human brain acquired with diffusion spectrum magnetic resonance imaging (MRI), one of the dMRI of high angular resolution available. These results will lead us to the conclusion that this new high-dimensional representation indeed simplifies the problem of segmentation and regularization.
Mots-clé
Algorithms, Artificial Intelligence, Brain/anatomy & histology, Diffusion Magnetic Resonance Imaging/methods, Humans, Image Enhancement/methods, Image Interpretation, Computer-Assisted/methods, Imaging, Three-Dimensional/methods, Nerve Fibers, Myelinated/ultrastructure, Pattern Recognition, Automated/methods, Reproducibility of Results, Sensitivity and Specificity
Pubmed
Web of science
Création de la notice
11/04/2008 13:22
Dernière modification de la notice
03/03/2018 18:41
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