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[2508.08177] MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision
Summary
The paper introduces MedReasoner, a framework that utilizes reinforcement learning for precise medical reasoning and pixel-level grounding in imaging, addressing limitations of current methods.
Why It Matters
MedReasoner represents a significant advancement in medical imaging by improving the accuracy of reasoning and grounding through reinforcement learning. This innovation is crucial for enhancing diagnostic processes and treatment planning, making it relevant for healthcare professionals and AI researchers alike.
Key Takeaways
- MedReasoner separates reasoning from segmentation, optimizing each through distinct methods.
- Introduces Unified Medical Reasoning Grounding (UMRG), a new vision-language task for clinical applications.
- Achieves state-of-the-art performance on the newly released U-MRG-14K dataset.
Computer Science > Computer Vision and Pattern Recognition arXiv:2508.08177 (cs) [Submitted on 11 Aug 2025 (v1), last revised 18 Feb 2026 (this version, v3)] Title:MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision Authors:Zhonghao Yan, Muxi Diao, Yuxuan Yang, Ruoyan Jing, Jiayuan Xu, Kaizhou Zhang, Lele Yang, Yanxi Liu, Kongming Liang, Zhanyu Ma View a PDF of the paper titled MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision, by Zhonghao Yan and 8 other authors View PDF HTML (experimental) Abstract:Accurately grounding regions of interest (ROIs) is critical for diagnosis and treatment planning in medical imaging. While multimodal large language models (MLLMs) combine visual perception with natural language, current medical-grounding pipelines still rely on supervised fine-tuning with explicit spatial hints, making them ill-equipped to handle the implicit queries common in clinical practice. This work makes three core contributions. We first define Unified Medical Reasoning Grounding (UMRG), a novel vision-language task that demands clinical reasoning and pixel-level grounding. Second, we release U-MRG-14K, a dataset of 14K samples featuring pixel-level masks alongside implicit clinical queries and reasoning traces, spanning 10 modalities, 15 super-categories, and 108 specific categories. Finally, we introduce MedReasoner, a modular framework that distinct...
