Modality cycles with masked conditional diffusion for unsupervised anomaly segmentation in MRI

Unsupervised anomaly segmentation aims to detect patterns that are distinct from any patterns processed during training, commonly called abnormal or out-of-distribution patterns, without providing any associated manual segmentations. Since anomalies during deployment can lead to model failure, detec...

詳細記述

書誌詳細
主要な著者: Liang, Z, Anthony, H, Wagner, F, Kamnitsas, K
フォーマット: Conference item
言語:English
出版事項: Springer 2024