This paper introduces Regional Deep Atrophy (RDA), an interpretable deep learning method that combines temporal inference from longitudinal MRI scans with an attention-based deformable registration network to highlight brain regions contributing to atrophy. While maintaining the accuracy of the earlier DeepAtrophy model, RDA improves clinical usability by offering insight into regional brain changes, potentially enhancing early detection and monitoring of Alzheimer’s disease progression and treatment effects.
