Self‐supervised out‐of‐distribution detection—Metal implants and other anomaly

The proposed method can be leveraged to detect both intra- and interclass OOD data from abdominal CT images and can assess the quality of CT datasets to provide actionable insights. This workflow is particularly valuable for nonshareable healthcare collaborations, where it can be deployed as a service within local firewalls for automated dataset curation without prior knowledge about the OOD types. The implementation of the algorithm is available in the GitHub: https://github.com/gokul-ramasamy/implant_detection.git.