Automatic extraction of proximal femur contours from calibrated X-ray images: a Bayesian inference approach

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Authors: Xiao Dong and Guoyan Zheng
Date: Aug. 2, 2009
Publisher: Inderscience Publishers Ltd.
Document Type: Article
Length: 111 words

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Abstract :

Byline: Xiao Dong, Guoyan Zheng 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.

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Gale Document Number: GALE|A228088922