Showing cs.CVShow all
3 papers · 1 filter
cs.CV2024
Language Models Meet Anomaly Detection for Better Interpretability and Generalizability
Jun Li, Su Hwan Kim, Philip Müller +5
This research explores the integration of language models and unsupervised anomaly detection in medical imaging, addressing two key questions: (1) Can language models enhance the i…
cs.CV2024
ChEX: Interactive Localization and Region Description in Chest X-rays
Philip Müller, Georgios Kaissis, Daniel Rueckert
Report generation models offer fine-grained textual interpretations of medical images like chest X-rays, yet they often lack interactivity (i.e. the ability to steer the generation…
cs.CV2024
Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI Pooling
Philip Müller, Felix Meissen, Georgios Kaissis +1
Weakly supervised object detection (WSup-OD) increases the usefulness and interpretability of image classification algorithms without requiring additional supervision. The successe…