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Segmentation of liver tumor via nonlocal active contours

Abstract : To reduce the manual labor time and provide the accuracy of liver tumor segmentation in the treatment planning of radiofrequency ablation (RFA), a novel method for liver tumor image segmentation by nonlocal active contours is proposed in this paper. A multi Gabor feature map of the liver tumor image is computed to describe the homogeneity of patches in a nonlocal way, and the nonlocal comparisons between pairs of patches are used to calculate the active contour energy. The whole energy function is minimized via a level set method to give the final segmentation. The experimental results indicate that the proposed method leads to good liver tumor segmentation with a good robustness to initialization condition. Experiment results show the proposed method can provide segmentation close to manual results, with the mean overlap error (OE) less than 23.86%
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https://hal-univ-rennes1.archives-ouvertes.fr/hal-01320722
Contributor : Laurent Jonchère <>
Submitted on : Tuesday, May 24, 2016 - 12:56:23 PM
Last modification on : Friday, July 5, 2019 - 10:16:02 AM

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B. Chen, Y. Chen, G. Yang, J. Meng, R. Zeng, et al.. Segmentation of liver tumor via nonlocal active contours. 2015 IEEE International Conference on Image Processing (ICIP), 2015, Quebec City, Canada. pp.3745--3748, ⟨10.1109/ICIP.2015.7351504⟩. ⟨hal-01320722⟩

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