title: A new hierarchical method for multi-level segmentation of bone in pelvic CT scans.
abstract: 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.
authors.affiliation: Computer Science Department, Virginia Commonwealth University, Richmond, VA 23220, USA. wuj6@ vcu.edu
authors.forename: Jie
authors.initials: J
authors.lastname: Wu
authors.forename: Pavani
authors.initials: P
authors.lastname: Davuluri
authors.forename: Kevin
authors.initials: K
authors.lastname: Ward
authors.forename: Charles
authors.initials: C
authors.lastname: Cockrell
authors.forename: Rosalyn
authors.initials: R
authors.lastname: Hobson
authors.forename: Kayvan
authors.initials: K
authors.lastname: Najarian
mesh_terms: D000465:Algorithms; D006801:Humans; D010388:Pelvis / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods*