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Spinal cord grey matter segmentation challenge., , , , , , , , , and 18 other author(s). NeuroImage, (2017)Unsupervised domain adaptation for medical imaging segmentation with self-ensembling., , , and . NeuroImage, (2019)What can we learn from T2* maps of the cortex?. NeuroImage, (2014)The current state-of-the-art of spinal cord imaging: Applications., , , , , , , , , and 13 other author(s). NeuroImage, (2014)OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization., , , , , , , , , and 2 other author(s). MICCAI (2), volume 10434 of Lecture Notes in Computer Science, page 712-719. Springer, (2017)Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections., , , , , , , , and . DLMIA/ML-CDS@MICCAI, volume 10553 of Lecture Notes in Computer Science, page 330-337. Springer, (2017)Geometric Evaluation of Distortion Correction Methods in Diffusion MRI of the Spinal Cord., , , , , , , and . ISBI, page 1696-1699. IEEE, (2019)U-Net Fixed-Point Quantization for Medical Image Segmentation., , , , , , and . LABELS/HAL-MICCAI/CuRIOUS@MICCAI, volume 11851 of Lecture Notes in Computer Science, page 115-124. Springer, (2019)Automatic spinal cord localization, robust to MRI contrasts using global curve optimization., , , , , , , , , and 2 other author(s). Medical Image Analysis, (2018)PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space., , , , , and . NeuroImage, (2018)