6 papers · 1 filter
MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
Shengyuan Liu, Liuxin Bao, Qi Yang +6
Medical image segmentation is evolving from task-specific models toward generalizable frameworks. Recent research leverages Multi-modal Large Language Models (MLLMs) as autonomous…
EndoBench: A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis
Shengyuan Liu, Boyun Zheng, Wenting Chen +5
Endoscopic procedures are essential for diagnosing and treating internal diseases, and multi-modal large language models (MLLMs) are increasingly applied to assist in endoscopy ana…
RadFabric: Agentic AI System with Reasoning Capability for Radiology
Wenting Chen, Yi Dong, Zhaojun Ding +14
Chest X ray (CXR) imaging remains a critical diagnostic tool for thoracic conditions, but current automated systems face limitations in pathology coverage, diagnostic accuracy, and…
Spatial-temporal Hierarchical Reinforcement Learning for Interpretable Pathology Image Super-Resolution
Wenting Chen, Jie Liu, Tommy W. S. Chow +1
Pathology image are essential for accurately interpreting lesion cells in cytopathology screening, but acquiring high-resolution digital slides requires specialized equipment and l…
Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning
Chong Ma, Hanqi Jiang, Wenting Chen +10
In the medical multi-modal frameworks, the alignment of cross-modality features presents a significant challenge. However, existing works have learned features that are implicitly…
Fine-Grained Image-Text Alignment in Medical Imaging Enables Explainable Cyclic Image-Report Generation
Wenting Chen, Linlin Shen, Jingyang Lin +3
To address these issues, we propose a novel Adaptive patch-word Matching (AdaMatch) model to correlate chest X-ray (CXR) image regions with words in medical reports and apply it to…