Brain-predicted age may be used as a potential biomarker of brain aging, and there also may be features related to cerebrovascular aging, such as decline of visualization of the arteries, or tortuosity. Therefore, the purpose of this study was to investigate whether there are learnable features by a deep convolutional neural network in the maximum intensity projection images of time-of-flight magnetic resonance angiography that might be associated with cerebrovascular aging.
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