DocumentCode
2463991
Title
Locally-Constrained Region-Based Methods for DW-MRI Segmentation
Author
Melonakos, John ; Niethammer, Marc ; Mohan, Vandana ; Kubicki, Marek ; Miller, James V. ; Tannenbaum, Allen
Author_Institution
Georgia Inst. of Technol., Atlanta
fYear
2007
fDate
14-21 Oct. 2007
Firstpage
1
Lastpage
8
Abstract
In this paper, we describe a method for segmenting fiber bundles from diffusion-weighted magnetic resonance images using a locally-constrained region based approach. From a pre-computed optimal path, the algorithm propagates outward capturing only those voxels which are locally connected to the fiber bundle. Rather than attempting to find large numbers of open curves or single fibers, which individually have questionable meaning, this method segments the full fiber bundle region. The strengths of this approach include its ease-of-use, computational speed, and applicability to a wide range of fiber bundles. In this work, we show results for segmenting the cingulum bundle. Finally, we explain how this approach and extensions thereto overcome a major problem that typical region-based flows experience when attempting to segment neural fiber bundles.
Keywords
biomedical MRI; brain; image segmentation; medical image processing; DW-MRI segmentation; diffusion-weighted magnetic resonance image; locally-constrained region based approach; neural fiber bundle; Bayesian methods; Biomedical computing; Biomedical imaging; Decision making; Hospitals; Image segmentation; Magnetic resonance; Signal to noise ratio; Stochastic resonance; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location
Rio de Janeiro
ISSN
1550-5499
Print_ISBN
978-1-4244-1630-1
Electronic_ISBN
1550-5499
Type
conf
DOI
10.1109/ICCV.2007.4409167
Filename
4409167
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