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kNN-based multi-spectral MRI brain tissue classification: manual training versus automated atlas-based training., , , , , , and . Medical Imaging: Image Processing, volume 6144 of SPIE Proceedings, page 61443L. SPIE, (2006)White matter lesion extension to automatic brain tissue segmentation on MRI., , , , , , , and . NeuroImage, 45 (4): 1151-1161 (2009)Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification., , , , , , , and . NeuroImage, 37 (1): 71-81 (2007)White matter atrophy and lesion formation explain the loss of structural integrity of white matter in aging., , , , , , , and . NeuroImage, 43 (3): 470-477 (2008)Statistical Analysis of Structural Brain Connectivity., , , , , , , , , and . MICCAI (2), volume 6362 of Lecture Notes in Computer Science, page 101-108. Springer, (2010)Automated localization of periventricular and subcortical white matter lesions., , , , , , , and . Medical Imaging: Image Processing, volume 6512 of SPIE Proceedings, page 651232. SPIE, (2007)Less head motion during MRI under task than resting-state conditions., , , , and . NeuroImage, (2017)You Are How You Walk: Quantifying Privacy Risks in Step Count Data., , , , and . CoRR, (2023)Automatic Segmentation of Brain Tissue Andwhitematter Lesions in MRI., , , , , , and . ISBI, page 652-655. IEEE, (2007)FatSegNet : A Fully Automated Deep Learning Pipeline for Adipose Tissue Segmentation on Abdominal Dixon MRI., , , , , , and . CoRR, (2019)