NDLI: Fast marching tractography from multiple diffusion sensitizing directions in MR-DTI from the brain

Content Provider	IEEE Xplore Digital Library
Author	Losnegard, A. Lundervold, A. Haasz, J. Hodneland, E.
Copyright Year	2011
Description	Author affiliation: Department of Biomedicine, University of Bergen, Norway (Losnegard, A.; Lundervold, A.; Haasz, J.; Hodneland, E.)
Abstract	Tractography of white matter fibers is a challenging task due to the complexity of fiber pathways, the resolution of the imaging techniques, and due to the difficulties associated with result verification. MR Diffusion Weighted Imaging (DWI) provides water diffusion estimates for many directions in each voxel. These estimates can be used to derive a tensor which gives information about the diffusion in three orthogonal directions in each voxel. However, some voxels contain fibers with varying directions, often referred to as crossing fibers. The approximated diffusion tensor in such voxels will often give insufficient information and lead a tractography algorithm in the wrong direction. Work has been done to compute two or more diffusion tensors to solve this problem, with varying success. We propose to use the MR diffusion measures for all directions instead of the tensor approximation approach, to be able to follow fibers correctly through voxels containing multiple fiber directions using the Fast-Marching (FM) method. Tests on synthetic data show that the proposed method demonstrates improved abilities to track crossing fibers in isotropic regions compared to standard methods.
Starting Page	497
Ending Page	500
File Size	3427384
Page Count	4
File Format	PDF
ISBN	9781457708411
ISSN	18455921
e-ISBN	9789531841597
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-04
Publisher Place	Croatia
Access Restriction	Subscribed
Subject Keyword	Frequency modulation Tensile stress Image reconstruction Diffusion tensor imaging Biomedical imaging Signal processing algorithms
Content Type	Text
Resource Type	Article

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