ISSN : 1796-2048
Volume : 2    Issue : 5    Date : September 2007

Automatic Extraction of Femur Contours from Calibrated X-Ray Images using Statistical Information
Xiao Dong, Miguel A. Gonzalez Ballester, and Guoyan Zheng
Page(s): 46-54
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Automatic identification and extraction of bone contours from x-ray images is an essential first step
task for further medical image analysis. In this paper we propose a 3D statistical model based
framework for the proximal femur contour extraction from calibrated x-ray images. The automatic
initialization to align the 3D model with the x-ray images is solved by an Estimation of Bayesian
Network Algorithm to fit a simplified multiple component geometrical model of the proximal femur to
the x-ray data. Landmarks can be extracted from the geometrical model for the initialization of the 3D
statistical model. The contour extraction is then accomplished by a joint registration and segmentation
procedure. We iteratively updates the extracted bone contours and an instanced 3D model to fit the
x-ray images. Taking the projected silhouettes of the instanced 3D model on the registered x-ray
images as templates, bone contours can be extracted by a graphical model based Bayesian
inference. The 3D model can then be updated by a non-rigid 2D/3D registration between the 3D
statistical model and the extracted bone contours. Preliminary experiments on clinical data sets
verified its validity.

Index Terms
contour extraction, statistical model, Bayesian network, 2D/3D registration, segmentation, calibrated
x-ray image