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Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?, , , и . CoRR, (2020)Label fusion and training methods for reliable representation of inter-rater uncertainty., , и . CoRR, (2022)2D Multi-Class Model for Gray and White Matter Segmentation of the Cervical Spinal Cord at 7T., , , , и . CoRR, (2021)Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers, , , , , , , , , и 81 other автор(ы). Scientific Data, (августа 2021)ivadomed: A Medical Imaging Deep Learning Toolbox., , , , , , и . CoRR, (2020)Impact of individual rater style on deep learning uncertainty in medical imaging segmentation., , и . CoRR, (2021)Automatic spinal cord localization, robust to MRI contrasts using global curve optimization., , , , , , , , , и 2 other автор(ы). Medical Image Anal., (2018)Benefits of Linear Conditioning for Segmentation using Metadata., , , , , и . MIDL, том 143 из Proceedings of Machine Learning Research, стр. 416-430. PMLR, (2021)OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization., , , , , , , , , и 2 other автор(ы). MICCAI (2), том 10434 из Lecture Notes in Computer Science, стр. 712-719. Springer, (2017)SoftSeg: Advantages of soft versus binary training for image segmentation., , и . CoRR, (2020)