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Population-wide principal component-based quantification of blood-brain-barrier dynamics in multiple sclerosis., , , , and . NeuroImage, 57 (4): 1430-1446 (2011)Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging., , , , , , , and . NeuroImage, (2016)In vivo quantification of T2⁎ anisotropy in white matter fibers in marmoset monkeys., , , , , , , and . NeuroImage, 59 (2): 979-985 (2012)Ex vivo MR microscopy of a human brain with multiple sclerosis: Visualizing individual cells in tissue using intrinsic iron., , , , and . NeuroImage, (2020)Topology preserving automatic segmentation of the spinal cord in magnetic resonance images., , , , , and . ISBI, page 1737-1740. IEEE, (2011)Fiber tractogrophy and tract segmentation in multiple sclerosis lesions., , , , and . ISBI, page 1488-1491. IEEE, (2011)Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?, , , , , , , , , and 1 other author(s). CoRR, (2022)Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks., , , , , , , , , and 42 other author(s). CoRR, (2018)Bayesian scalar-on-image regression with application to association between intracranial DTI and cognitive outcomes., , , , and . NeuroImage, (2013)A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions., , , , , and . NeuroImage, 49 (2): 1524-1535 (2010)