Unsupervised learning can discover various diseases, relying on large-scale unannotated
medical images of healthy subjects. Towards this, unsupervised methods reconstruct a
single medical image to detect outliers either in the learned feature space or from high
reconstruction loss. However, without considering continuity between multiple adjacent
slices, they cannot directly discriminate diseases composed of the accumulation of subtle
anatomical anomalies, such as Alzheimer's Disease (AD). Moreover, no study has shown …