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Automatic and robust forearm segmentation using graph cuts

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6 Author(s)
P. Furnstahl ; Computer Vision Laboratory, ETH Zurich, Switzerland ; T. Fuchs ; A. Schweizer ; L. Nagy
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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.

Published in:

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

Date of Conference:

14-17 May 2008