Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/1416
We present in this paper an application of minimal surfaces and
Markov random fields to the segmentation of liver tumors. The
originality of the work consists in applying these models to the
region adjacency graph of a watershed transform. We detail the
assumptions and the approximations introduced in these models by
using a region graph instead of a pixel graph. This strategy leads
to an interactive method that we use to delineate tumors in 3D CT
images. We detail our strategy to achieve relevant segmentations of
these structures and compare our results to hand made segmentations
done by experienced radiologists. This paper summarizes our
participation to the MICCAI 2008 workshop called: "3D segmentation in the clinic : A
Grand Challenge II".

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plus my review by Xiang Deng on 07-25-2008 for revision #3
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Categories: Feature extraction, Segmentation, Watersheds
Keywords: Watershed, graph cuts
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