Paper Info
Title
Representing diffusion MRI in 5-D simplifies regularization and segmentation of white matter tracts.
Abstract
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.
Year
DOI
Venue
2007
10.1109/TMI.2007.899168
IEEE Trans. Med. Imaging
Keywords
Field
DocType
biomedical MRI,brain,image segmentation,medical image processing,neurophysiology,angular resolution,crossing liber tracts,denoising,diffusion magnetic resonance imaging,diffusion spectrum,human brain,nonEuclidean space,regularization,segmentation,white matter tracts,diffusion magnetic resonance imaging (MRI),five dimensional level sets,white matter segmentation and position orientation space
Noise reduction,Computer vision,Diffusion MRI,Scale-space segmentation,Segmentation,Scalar (physics),Level set,Image segmentation,Regularization (mathematics),Artificial intelligence,Mathematics
Journal
Volume
Issue
ISSN
26
11
0278-0062
Citations 
PageRank 
References 
8
1.07
8
Authors
5
Name
Order
Citations
PageRank
Lisa Jonasson11127.53
Xavier Bresson2184268.08
Jean-Philippe Thiran32320257.56
Van Jay Wedeen418312.20
P. Hagmann551135.38