Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed

Abstract : 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 adja-cency 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 used 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 3 workshop called: " 3D segmentation in the clinic : A Grand Challenge II " .
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Communication dans un congrès
11th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2008), Sep 2008, New York, NY, United States. Lecture Notes in Computer Science 2008, 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings
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https://hal-mines-paristech.archives-ouvertes.fr/hal-01445751
Contributeur : Etienne Decencière <>
Soumis le : mercredi 25 janvier 2017 - 12:12:17
Dernière modification le : mardi 12 septembre 2017 - 11:40:57
Document(s) archivé(s) le : mercredi 26 avril 2017 - 14:03:09

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Jean Stawiaski, Etienne Decencière, François Bidault. Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed. 11th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2008), Sep 2008, New York, NY, United States. Lecture Notes in Computer Science 2008, 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings. <hal-01445751>

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