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Computational and Mathematical Methods in MedicineVolume 2013 2013, Article ID 547897, 6 pages

Research Article

Université de Rouen, LITIS EA 4108, 22 Boulevard Gambetta, 76183 Rouen Cedex, France

Centre Henri Becquerel, rue d-Amiens, 76038 Rouen Cedex 1, France

Received 14 May 2013; Accepted 30 July 2013

Academic Editor: Liang Li

Copyright © 2013 Damien Grosgeorge et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper, we focus on esophagus segmentation, a challenging application since the wall of the esophagus, made of muscle tissue, has very low contrast in CT images. We propose in this paper an original method to segment in thoracic CT scans the 3D esophagus using a skeleton-shape model to guide the segmentation. Our method is composed of two steps: a 3D segmentation by graph cut with skeleton prior, followed by a 2D propagation. Our method yields encouraging results over 6 patients.

Autor: Damien Grosgeorge, Caroline Petitjean, Bernard Dubray, and Su Ruan



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