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2005
Springer

Representing Diffusion MRI in 5D for Segmentation of White Matter Tracts with a Level Set Method

10 years 3 days ago
Representing Diffusion MRI in 5D for Segmentation of White Matter Tracts with a Level Set Method
We present a method for segmenting white matter tracts from high angular resolution diffusion MR images by representing the data in a 5 dimensional space of position and orientation. Whereas crossing fiber tracts cannot be separated in 3D position space, they clearly disentangle in 5D position-orientation space. The segmentation is done using a 5D level set method applied to hyper-surfaces evolving in 5D position-orientation space. In this paper we present a methodology for constructing the positionorientation space. We then show how to implement the standard level set method in such a non-Euclidean high dimensional space. The level set theory is basically defined for N-dimensions but there are several practical implementation details to consider, such as mean curvature. Finally, we will show results from a synthetic model and a few preliminary results on real data of a human brain acquired by high angular resolution diffusion MRI.
Lisa Jonasson, Patric Hagmann, Xavier Bresson, Jea
Added 16 Nov 2009
Updated 16 Nov 2009
Type Conference
Year 2005
Where IPMI
Authors Lisa Jonasson, Patric Hagmann, Xavier Bresson, Jean-Philippe Thiran, Van J. Wedeen
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