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What can we learn from T2* maps of the cortex?. NeuroImage, (2014)Unsupervised domain adaptation for medical imaging segmentation with self-ensembling., , , and . NeuroImage, (2019)Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers, , , , , , , , , and 81 other author(s). Scientific Data, (August 2021)Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?, , , , , , , , , and 1 other author(s). CoRR, (2022)Impact of individual rater style on deep learning uncertainty in medical imaging segmentation., , and . CoRR, (2021)ivadomed: A Medical Imaging Deep Learning Toolbox., , , , , , and . CoRR, (2020)Spine intervertebral disc labeling using a fully convolutional redundant counting model., , , and . CoRR, (2020)The current state-of-the-art of spinal cord imaging: Applications., , , , , , , , , and 13 other author(s). NeuroImage, (2014)Spinal cord grey matter segmentation challenge., , , , , , , , , and 18 other author(s). NeuroImage, (2017)Cortico-spinal imaging to study pain., , and . NeuroImage, (2021)