Stochastic Siamese MAE Pretraining for Longitudinal Medical Images
STAMP is a novel Siamese MAE framework that learns temporal disease progression in 3D medical scans from just two visits. It captures long-term, unpredictable changes by using a stochastic process conditioned on the time difference between images. This allows the model to predict future disease states from a single baseline scan, improving personalized monitoring.