Brain-predicted age may be used as a potential biomarker of brain aging. Given that 2D T2-weighted images are more routinely acquired from patients than those 3D images, this study investigated the potential applicability of 2D images in deep learning-based prediction of brain age with an assumption that each individual slice of the T2-weighted brain images possesses brain age-associated features learnable by a convolutional neural network (CNN). The purpose of this study was to investigate whether there are learnable features by a CNN in each slice of routine T2-weighted spin-echo brain MR images that might be associated with normal aging.
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