ICIP 2006, Atlanta, GA
 

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Paper:TP-P3.2
Session:Biomedical Image Segmentation and Quantitative Analysis
Time:Tuesday, October 10, 14:20 - 17:00
Presentation: Poster
Topic: Biomedical Imaging: Biomedical image segmentation and quantitative analysis
Title: SEMI-AUTOMATIC 3-D SEGMENTATION OF ANATOMICAL STRUCTURES OF BRAIN MRI VOLUMES USING GRAPH CUTS
Authors: Huy-Nam Doan; Georgia Institute of Technology 
 Greg Slabaugh; Siemens Corporate Research, Inc. 
 Gozde Unal; Siemens Corporate Research, Inc. 
 Tong Fang; Siemens Corporate Research, Inc. 
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.