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====== Applications of Belief Functions ====== | ====== Applications of Belief Functions ====== | ||
- | - C. Lian, S. Ruan, T. Denoeux, H. Li, and P. Vera, " | + | - L. Huang, S. Ruan and T. Denoeux. Belief function-based semi-supervised learning for brain tumor segmentation. 2021 IEEE International Symposium on Biomedical Imaging (ISBI 2021), Nice, France, IEEE, 2021. {{ : |
+ | - C. Lian, S. Ruan, T. Denoeux, Y. Guo and P. Vera. Accurate segmentation in FDG-PET images with guidance of complementary CT images. 2017 IEEE International Conference on Image Processing (ICIP 2017), Beijing, China, IEEE, 2017. {{: | ||
+ | - C. Lian, S. Ruan, T. Denoeux, H. Li and P. Vera. Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive | ||
+ | - C. Lian, S. Ruan, T. Denoeux, H. Li, and P. Vera, " | ||
- C. Lian, H. Li, T. Denoeux, P. Vera and S. Ruan, Dempster-Shafer Theory based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy, 18th International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI-2015), | - C. Lian, H. Li, T. Denoeux, P. Vera and S. Ruan, Dempster-Shafer Theory based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy, 18th International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI-2015), | ||
- C. Lian, S. Ruan, T. Denoeux and P. Vera. Outcome prediction in tumour therapy based on Dempster-Shafer Theory. | - C. Lian, S. Ruan, T. Denoeux and P. Vera. Outcome prediction in tumour therapy based on Dempster-Shafer Theory. |