2 papers
cs.CV2026
HiMatch-AD: DINOv3-driven Hierarchical Matching for Training-free Medical Anomaly Detection
Jiayu Huo, Jingyuan Hong, Meng Zhou +2
Anomaly detection is essential for medical image analysis, where pathological regions often appear as rare deviations from normal anatomical structures. While training-based method…
eess.IV2026
DINO-AD: Unsupervised Anomaly Detection with Frozen DINO-V3 Features
Jiayu Huo, Jingyuan Hong, Liyun Chen
Unsupervised anomaly detection (AD) in medical images aims to identify abnormal regions without relying on pixel-level annotations, which is crucial for scalable and label-efficien…