5 papers
CURE: Curriculum-guided Multi-task Training for Reliable Anatomy Grounded Report Generation
Pablo Messina, Andrés Villa, Juan León Alcázar +5
Medical vision-language models can automate the generation of radiology reports but struggle with accurate visual grounding and factual consistency. Existing models often misalign…
Perceptual Evaluation of GANs and Diffusion Models for Generating X-rays
Gregory Schuit, Denis Parra, Cecilia Besa
Generative image models have achieved remarkable progress in both natural and medical imaging. In the medical context, these techniques offer a potential solution to data scarcity-…
A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
Ivania Donoso-Guzmán, Kristýna Sirka Kacafírková, Maxwell Szymanski +3
Despite promising developments in Explainable Artificial Intelligence, the practical value of XAI methods remains under-explored and insufficiently validated in real-world settings…
CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray
Mingquan Lin, Gregory Holste, Song Wang +30
The CXR-LT series is a community-driven initiative designed to enhance lung disease classification using chest X-rays (CXR). It tackles challenges in open long-tailed lung disease…
Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation
Pablo Messina, René Vidal, Denis Parra +2
Advancing representation learning in specialized fields like medicine remains challenging due to the scarcity of expert annotations for text and images. To tackle this issue, we pr…