4 papers
MMRareBench: A Rare-Disease Multimodal and Multi-Image Medical Benchmark
Junzhi Ning, Jiashi Lin, Yingying Fang +9
Multimodal large language models (MLLMs) have advanced clinical tasks for common conditions, but their performance on rare diseases remains largely untested. In rare-disease scenar…
Seeing Through Experts Eyes A Foundational Vision Language Model Trained on Radiologists Gaze and Reasoning
Kinhei Lee, Peiyuan Jing, Zhenxuan Zhang +5
Large scale vision language models have shown promise in automating chest Xray interpretation, yet their clinical utility remains limited by a gap between model outputs and radiolo…
Learning Robust Visual Features in Computed Tomography Enables Efficient Transfer Learning for Clinical Tasks
Rubén Moreno-Aguado, Alba Magallón, Victor Moreno +2
There is substantial interest in developing artificial intelligence systems to support radiologists across tasks ranging from segmentation to report generation. Existing computed t…
Enhancing Weakly Supervised Semantic Segmentation for Fibrosis via Controllable Image Generation
Zhiling Yue, Yingying Fang, Liutao Yang +3
Fibrotic Lung Disease (FLD) is a severe condition marked by lung stiffening and scarring, leading to respiratory decline. High-resolution computed tomography (HRCT) is critical for…