Automatic Extraction of Proximal Femur Contours from Calibrated X-Ray Images Using 3D Statistical Models

  • Xiao Dong
  • Guoyan Zheng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5128)


Automatic identification and extraction of bone contours from x-ray images is the first essential 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 initialization is solved by an Estimation of Bayesian Network Algorithm to fit a multiple component geometrical model to the x-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the x-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Our experimental results demonstrate its performance and efficacy even when part of the images are occluded.


statistical models segmentation fluoroscopy Bayesian network 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Xiao Dong
    • 1
  • Guoyan Zheng
    • 1
  1. 1.MEM Research CenterUniversity of BernSwitzerland

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