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Conference Papers Year : 2015

Segmentation of liver tumor via nonlocal active contours


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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Dates and versions

hal-01320722 , version 1 (24-05-2016)



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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