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Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains.

, , , , , , , , , , , , and . NeuroImage, (2022)

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Accurate and Explainable Image-Based Prediction Using a Lightweight Generative Model., , , , and . MICCAI (8), volume 13438 of Lecture Notes in Computer Science, page 448-458. Springer, (2022)Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images., , , , , , , , and . MICCAI (8), volume 14227 of Lecture Notes in Computer Science, page 226-236. Springer, (2023)A Longitudinal Method for Simultaneous Whole-Brain and Lesion Segmentation in Multiple Sclerosis., , , , and . MLCN/RNO-AI@MICCAI, volume 12449 of Lecture Notes in Computer Science, page 119-128. Springer, (2020)Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations., , , , , , , , , and 2 other author(s). MICCAI (8), volume 14227 of Lecture Notes in Computer Science, page 173-183. Springer, (2023)An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation., , , , , , and . CoRR, (2022)Intra- and interscanner variability of magnetic resonance imaging based volumetry in multiple sclerosis., , , , , , , , , and 3 other author(s). NeuroImage, (2016)Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains., , , , , , , , , and 3 other author(s). NeuroImage, (2022)