期刊
MEDICAL IMAGE ANALYSIS
卷 14, 期 1, 页码 13-20出版社
ELSEVIER
DOI: 10.1016/j.media.2009.09.002
关键词
Liver tumor segmentation; Liver metastasis segmentation; Level set method; Spiral-scanning technique
类别
资金
- Flemish Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT Vlaanderen)
- Research Fund K. U. Leuven
In this paper, a specific method is presented to facilitate the semi-automatic segmentation of liver tumors and liver metastases in CT images. Accurate and reliable segmentation of tumors is essential for the follow-up of cancer treatment. The core of the algorithm is a level set method. The initialization is generated by a spiral-scanning technique based on dynamic programming. The level set evolves according to a speed image that is the result of a statistical pixel classification algorithm with supervised learning. This method is tested on CT images of the abdomen and compared with manual delineations of liver tumors. The described method outperformed the semi-automatic methods of the other participants of the 3D Liver Tumor Segmentation Challenge 2008. Evaluating the algorithm on the provided test data leads to an average overlap error of 32.6% and an average volume difference of 17.9%. The average, the RMS and the maximum surface distance are 2.0, 2.6 and 10.1 mm, respectively. (C) 2009 Elsevier B. V. All rights reserved.
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