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Automatic and Robust Forearm Segmentation using Graph Cuts

P. Fuernstahl, T. Fuchs, A. Schweizer, L. Nagy, G. Székely and M. Harders
Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on
May 2008

Abstract

The segmentation of bones in computed tomography (CT) images is an important step for the simulation of forearm bone motion, since it allows to include patient specific anatomy in a kinematic model. While the identification of the bone diaphysis is straightforward, the segmentation of bone joints with weak, thin, and diffusive boundaries is still a challenge. We propose a graph cut segmentation approach that is particularly suited to robustly segment joints in 3-d CT images. We incorporate knowledge about intensity, bone shape and local structures into a novel energy function. Our presented framework performs a simultaneous segmentation of both forearm bones without any user interaction.


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@InProceedings{eth_biwi_00549,
  author = {P. Fuernstahl and T. Fuchs and A. Schweizer and L. Nagy and G. Székely and M. Harders},
  title = {Automatic and Robust Forearm Segmentation using Graph Cuts},
  booktitle = {Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on},
  year = {2008},
  month = {May},
  pages = {77-80},
  publisher = {IEEE},
  keywords = {}
}