DocumentCode :
617309
Title :
Multi-Tensor Field spectral segmentation for white matter fiber bundle classification
Author :
Ocegueda, Omar ; Rivera, Marco
Author_Institution :
Centro de Investig. en Mat. Guanajuato, Guanajuato, Mexico
fYear :
2013
fDate :
7-11 April 2013
Firstpage :
262
Lastpage :
265
Abstract :
We present an algorithm for segmenting the white-matter axon fiber bundles from HARDI images. We formulate the segmentation problem as a Multi-Tensor Field segmentation problem in which the compartments of each Multi-Tensor may belong to different classes, allowing the algorithm to handle crossing fiber tracts. Experimental results on two publicly available synthetic datasets and the fiber-cup phantom show that fiber crossings can be effectively separated by using this approach, and preliminary results on real data show that the segmentation obtained is consistent with known anatomical structures.
Keywords :
biodiffusion; biomedical MRI; brain; image classification; image segmentation; medical image processing; phantoms; tensors; HARDI image; anatomical structure; fiber tract; fiber-cup phantom; multitensor field spectral segmentation; real data; synthetic dataset; white matter axon fiber bundle classification; Image segmentation; Magnetic resonance imaging; Nerve fibers; Phantoms; Tensile stress; Vectors; Brain imaging; Image segmentation; Tensor and vector field analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on
Conference_Location :
San Francisco, CA
ISSN :
1945-7928
Print_ISBN :
978-1-4673-6456-0
Type :
conf
DOI :
10.1109/ISBI.2013.6556462
Filename :
6556462
Link To Document :
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