Élise Bannier

Unsupervised deep generative models for anomaly detection in neuroimaging: A systematic scoping review

Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly investigated for identifying pathological brain abnormalities without requiring voxel-level annotations. By learning the distribution of healthy anatomy and generating pseudo-healthy reconstructions, these methods aim to local...