Transformed domain convolutional neural network for Alzheimer's disease diagnosis using structural MRI

•Investigated Jacobian transformation to identify distinctive features from structural magnetic resonance imaging (sMRI) data.•Fused Jacobian map with deep learning, which provided a quantitative measure for localized brain volume change and eventually built strong transformed domain classifier.•Proposed a whole brain JD-CNN framework that neither required identification of discriminative landmark (LM) locations nor any region of interests (ROIs).•Superior AD classification performance has been achieved as compared with previously reported state-of-the-art techniques.