Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior
This work introduces a latent spatial anomaly mask that models pixel-wise consistency between a test image and its latent corresponding pseudo-healthy image, and proposes an approximation of the unknown generation process that links healthy anatomy, anomalies, and the observed image, enabling a well-defined likelihood...