1. Abdallah, N., Xu, H., Marion, J.-M., Tauber, C., Carlier, T., Chauvet, P., Lu, L., Hatt, M., 2022. Predicting progression-free survival from FDG PET/CT images in head and neck cancer : comparison of different pipelines and harmonization strategies in the HECKTOR 2021 challenge dataset. In: Proceedings of the IEEE NSS-MIC.
2. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach;Aerts;Nat. Commun.,2014
3. Akiba, T., Sano, S., Yanase, T., Ohta, T., Koyama, M., 2019. Optuna: A Next-generation Hyperparameter Optimization Framework. In: Proceedings of the 25rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
4. A coarse-to-fine framework for head and neck tumor segmentation in CT and PET images;An,2022
5. Multi-task deep segmentation and radiomics for automatic prognosis in head and neck cancer;Andrearczyk,2021