BMAD: Benchmarks for Medical Anomaly Detection

arXiv:2306.11876v3 Announce Type: replace-cross
Abstract: Anomaly detection (AD) is a fundamental research problem in machine learning and computer vision, with practical applications in industrial inspection, video surveillance, and medical diagnosis. In medical imaging, AD is especially vital for detecting and diagnosing anomalies that may indicate rare diseases or conditions. However, there is a lack of a universal and fair benchmark for evaluating AD methods on medical images, which hinders the development of more generalized and robust AD methods in this …

anomaly anomaly detection arxiv benchmarks cs.cv detection eess.iv medical type