MIAS-SAM: Medical Image Anomaly Segmentation without thresholding
MIAS-SAM exploits the zero-shot segmentation capabilities of segment-anything to obtain accurate anomaly segmentations in an unsupervised way.
Jul 25, 2025
LoRIS - Weakly-Supervised Anomaly Detection for Ultrasound Images
LoRIS is a weakly-supervised anomaly detection method for knee ultrasound images. Trained only on nondistended cases, it uses a location prior to guide reconstruction and detect anomalies. It outperforms unsupervised methods and matches supervised ones—without needing segmentation annotations or images from both classes.
Oct 5, 2024