2 papers
cs.CV2026
Unsupervised Anomaly Detection for Image Dataset Quality Assurance in Multi-Center Breast MRI
Chiara Tappermann, Steffen Renisch, Lars Ole Schwen +3
Corrupted, inconsistent, or anomalous data silently threatens the safety and reliability of medical AI. Despite growing regulatory recognition of dataset quality assurance (QA) for…
cs.CV2026
RadYOLO: Computationally Efficient 3D Object Detection and Segmentation in CT and MRI
Kai Geissler, Laurens Müller-Groh, Hans Meine
Object detection and segmentation in three-dimensional medical images is a very active area of research. However, most proposed deep learning models carry a high computational cost…