Generative Modeling of Neurodegenerative Brain Anatomy with 4D Longitudinal Diffusion Model

ArXi:2604.22700v1 Announce Type: new Understanding and predicting the progression of neurodegenerative diseases remains a major challenge in medical AI, with significant implications for early diagnosis, disease monitoring, and treatment planning. However, most available longitudinal neuroimaging datasets are temporally sparse with a few follow-up scans per subject. This scarcity of temporal data limits our ability to model and accurately capture the continuous anatomical changes related to disease progression in individual subjects.