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Trustworthy Deep Learning for Medical Image Segmentation.. CoRR, (2023)A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation., , , , , , , , , and 11 other author(s). CoRR, (2022)Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings., , , , , , , , , and 7 other author(s). BrainLes@MICCAI, volume 13769 of Lecture Notes in Computer Science, page 3-13. Springer, (2022)SGD with Hardness Weighted Sampling for Distributionally Robust Deep Learning., , and . CoRR, (2020)Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging., , , , , , , , , and 30 other author(s). CoRR, (2020)Partial supervision for the FeTA challenge 2021., , , , , , and . CoRR, (2021)Label-Set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation., , , , , , , , , and 2 other author(s). MICCAI (2), volume 12902 of Lecture Notes in Computer Science, page 647-657. Springer, (2021)Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for Brain Tumor Segmentation: BraTS 2020 Challenge., , and . BrainLes@MICCAI (2), volume 12659 of Lecture Notes in Computer Science, page 200-214. Springer, (2020)NiftyNet: a deep-learning platform for medical imaging., , , , , , , , , and 7 other author(s). Comput. Methods Programs Biomed., (2018)Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients., , , , , , , , , and 12 other author(s). CoRR, (2020)