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A new hierarchical method for multi-level segmentation of bone in pelvic CT scans

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6 Author(s)
Jie Wu ; Computer Science Department, Virginia Commonwealth University, Richmond, VA 23220, USA ; Pavani Davuluri ; Kevin Ward ; Charles Cockrell
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Pelvic bone segmentation is a vital step in analyzing pelvic CT images and assisting physicians with diagnostic decisions in traumatic pelvic injuries. A new hierarchical segmentation algorithm is proposed using a template-based best shape matching method and Registered Active Shape Model (RASM) to automatically extract pelvic bone tissues from multi-level pelvic CT images. A novel hierarchical initialization process for RASM is proposed. 449 CT images across seven patients are used to test and validate the reliability and robustness of the proposed method. The segmentation results show that the proposed method performs better with higher accuracy than standard ASM method.

Published in:

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Date of Conference:

Aug. 30 2011-Sept. 3 2011