Title: Automatic extraction of proximal femur contours from calibrated X-ray images: a Bayesian inference approach
Authors: Xiao Dong, Guoyan Zheng
Addresses: ARTORG Center – ISTB, University of Bern, Stauffacherstrasse 78, CH-3014, Bern, Switzerland. ' ARTORG Center – ISTB, University of Bern, Stauffacherstrasse 78, CH-3014, Bern, Switzerland
Abstract: Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. This paper proposed a 3D-statistical-model-based framework for the proximal femur bone contour extraction from calibrated X-ray images. The initialisation to align the statistical model is solved by a particle filter on a dynamic Bayesian network to fit a multiple component geometrical model to the X-ray images. The contour extraction is accomplished by a non-rigid 2D–3D registration between the X-ray images and the statistical model, in which bone contours are extracted by a graphical-model-based Bayesian inference. Experiments on clinical data set verified its robustness against occlusion.
Keywords: contour extraction; statistical modelling; Bayesian networks; 2D–3D registration; segmentation; calibrated X-ray images; proximal femur contours; bone contours; medical image analysis; occlusion.
International Journal of Functional Informatics and Personalised Medicine, 2009 Vol.2 No.2, pp.231 - 240
Published online: 02 Aug 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article