Keywords: Machine Learning/Artificial Intelligence, BrainImage registration is currently employed to assist with diagnostic tasks such as neurodegenerative disease diagnosis. Aging also affects the brain, and our knowledge of age-related brain diseases is currently encumbered by age-induced bias; understanding the mechanisms of neurodegenerative diseases requires a deeper understanding of aging. Thus we have devised a pipeline for generating age-specific templates using a novel deep-learning algorithm detailed in a separate report. Our results show qualitative changes in brain morphology across age groups, and tissue segmentation was performed on each template to calculate volumetric changes in brain matter across time.
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