DocumentCode :
1570556
Title :
Semi-Automatic 3-D Segmentation of Anatomical Structures of Brain MRI Volumes using Graph Cuts
Author :
Doan, H. -N. ; Slabaugh, Greg ; Unal, G. ; Fang, Tao
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
fYear :
2006
Firstpage :
1913
Lastpage :
1916
Abstract :
We present a semi-automatic segmentation technique of the anatomical structures of the brain: cerebrum, cerebellum, and brain stem. The method uses graph cuts segmentation with an anatomic template for initialization. First, a skull stripping procedure is applied to remove non-brain tissues. Then, the segmentation is done hierarchically by first, extracting first the cerebrum from the brain, and then from the remaining volume the cerebellum and the brain stem are separated. This method is fast and can separate different anatomical structures of the brain in spite of weak boundaries. We describe our approach and present experimental results demonstrating its usefulness.
Keywords :
biomedical MRI; brain; image segmentation; medical image processing; neurophysiology; MRI; brain anatomical structure; brain stem; cerebellum; cerebrum; graph cuts; magnetic resonance imaging; semiautomatic 3-D segmentation; Active contours; Anatomical structure; Brain; Computational intelligence; Image segmentation; Intelligent structures; Magnetic resonance imaging; Robustness; Shape; Skull; Biomedical image processing; Image segmentation; Magnetic resonance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1522-4880
Print_ISBN :
1-4244-0480-0
Type :
conf
DOI :
10.1109/ICIP.2006.313142
Filename :
4106929
Link To Document :
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