Localized statistics for DW-MRI fiber bundle segmentation

We describe a method for segmenting neural fiber bundles in diffusion-weighted magnetic resonance images (DW-MRI). As these bundles traverse the brain to connect regions, their local orientation of diffusion changes drastically, hence a constant global model is inaccurate. We propose a method to com...

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Bibliographic Details
Published in2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops pp. 1 - 8
Main Authors Lankton, S., Melonakos, J., Malcolm, J., Dambreville, S., Tannenbaum, A.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.01.2008
Subjects
Active contours
Biomedical computing
Biomedical imaging
Brain modeling
Decision making
Image segmentation
Magnetic resonance
Statistical distributions
Statistics
Tensile stress
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Summary:We describe a method for segmenting neural fiber bundles in diffusion-weighted magnetic resonance images (DW-MRI). As these bundles traverse the brain to connect regions, their local orientation of diffusion changes drastically, hence a constant global model is inaccurate. We propose a method to compute localized statistics on orientation information and use it to drive a variational active contour segmentation that accurately models the non-homogeneous orientation information present along the bundle. Initialized from a single fiber path, the proposed method proceeds to capture the entire bundle. We demonstrate results using the technique to segment the cingulum bundle and describe several extensions making the technique applicable to a wide range of tissues.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISBN:9781424423392
1424423392
ISSN:2160-7508
1063-6919
1063-6919
2575-7075
DOI:10.1109/CVPRW.2008.4562999