DocumentCode :
2116414
Title :
Classification trees for fast segmentation of DTI brain fiber tracts
Author :
Zimmerman-Moreno, Gali ; Mayer, Arnaldo ; Greenspan, Hayit
Author_Institution :
Dept. of Biomed. Eng., Tel-Aviv Univ., Tel-Aviv
fYear :
2008
fDate :
23-28 June 2008
Firstpage :
1
Lastpage :
7
Abstract :
A method is proposed for modeling and classification of White Matter fiber tracts in the brain. The presented scheme uses classification trees in conjunction with spatial representation of the individual fibers, in order to capture the characteristic behavior of fibers belonging to a specific anatomical structure. The method is characterized by high classification speed, under 3 seconds for all the fibers in a typical DTI of a brain. The model has the ability to represent complex geometric structures and has an intuitive interpretation. Encouraging results are demonstrated for tract classification on real data from ten different subjects.
Keywords :
biomedical MRI; brain; image classification; image segmentation; medical image processing; DTI brain fiber tract segmentation; MRI brain; classification trees; complex geometric structures; diffusion tensor imaging; spatial representation; white matter; Anatomical structure; Biomedical engineering; Brain modeling; Classification tree analysis; Data mining; Diffusion tensor imaging; Image reconstruction; Magnetic resonance imaging; Solid modeling; Tensile stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location :
Anchorage, AK
ISSN :
2160-7508
Print_ISBN :
978-1-4244-2339-2
Electronic_ISBN :
2160-7508
Type :
conf
DOI :
10.1109/CVPRW.2008.4562998
Filename :
4562998
Link To Document :
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