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====== Applications of Belief Functions ====== | ====== Applications of Belief Functions ====== | ||
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+ | - L. Huang, T. Denoeux, D. Tonnelet, P. Decazes and S. Ruan. Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation. In C. Lian et al. (Eds), Machine Learning in Medical Imaging, Springer International Publishing", | ||
+ | Cham, pages 30-39, 2021. {{ : | ||
+ | - L. Huang, S. Ruan, P. Decazes and T. Denoeux. Evidential Segmentation of 3D PET/CT Images. In T. Denoeux, E. Lefèvre, Zh. Liu and F. Pichon (Eds), Belief Functions: Theory and Applications, | ||
+ | - L. Huang, S. Ruan and T. Denoeux. Covid-19 Classification with Deep Neural Network and Belief Functions. Fifth International Conference on Biological Information and Biomedical Engineering (BIBE 2021), July 20–22, 2021, Hangzhou, China. {{ : | ||
+ | - 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. 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, 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. |