title: Automated detection and segmentation of diaphyseal bone fragments from registered C-arm images for long bone fracture reduction.
abstract: Automated identification, pose and size estimation, and contour extraction of diaphyseal bone fragments can greatly improve the usability of a computer-assisted fluoroscopy-based navigation system for long bone fracture reduction. In this paper, a two step solution is proposed. The pose and size of a diaphyseal fragment are estimated through 3D morphable object fitting using a parametric cylinder model. The result of fragment identification is then fed to a region information based active contour model to extract the fragment contour. Experimental results show a promising accuracy and robustness of the proposed approach.
authors.affiliation: MEM Research Center, University of Bern, Stauffacherstrasse 78, CH-3014 Bern, Switzerland. E-mail: Guoyan.Zheng@MEMcenter.unibe.ch.
authors.forename: Guoyan
authors.initials: G
authors.lastname: Zheng
authors.forename: Xiao
authors.initials: X
authors.lastname: Dong
authors.forename: Xuan
authors.initials: X
authors.lastname: Zhang
authors.forename: L-P
authors.initials: LP
authors.lastname: Nolte