医学 AI

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson, Maria T. Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A. Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie L. Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme

专题命中 医疗多模态 ：healthcare AI(title,abstract)；radiology(title,abstract)；medical image(abstract)

Comments to appear at CHI 2024

Contrastive Regularization over LoRA for Multimodal Biomedical Image Incremental Learning

Haojie Zhang, Yixiong Liang, Hulin Kuang, Lihui Cen, Zhe Qu, Yigang Cen, Min Zeng, Shichao Kan

机构 * School of Computer Science and Engineering, Central South University（计算机科学与工程学院，中南大学） ； School of Automation, Central South University（自动化学院，中南大学） ； School of Computer Science and Technology, Beijing Jiaotong University（计算机科学与技术学院，北京交通大学） 纠错

专题命中 医疗多模态 ：medical image(title,abstract)；biomedical(title,abstract)；分类 cs.CV、cs.LG

Comments 10 pages, 3 figures, submitted to ACM Multimedia 2025

3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks

Xiaotang Gai, Jiaxiang Liu, Yichen Li, Zijie Meng, Jian Wu, Zuozhu Liu

机构 * ZJU-Angelalign R&D Center for Intelligence Healthcare（浙江大学智能医疗研发中心） ； Zhejiang University（浙江大学） ； Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence（浙江省医学影像人工智能重点实验室） ； Guangdong Institute of Intelligence Science and Technology（广东省智能科学与技术研究院） 纠错

专题命中 医疗多模态 ：radiology(title,abstract)；medical AI(abstract)；CT(abstract)；diagnosis(abstract)

Comments Accepted by NeurIPS 2025

MicarVLMoE: A Modern Gated Cross-Aligned Vision-Language Mixture of Experts Model for Medical Image Captioning and Report Generation

Amaan Izhar, Nurul Japar, Norisma Idris, Ting Dang

机构 * Faculty of Computer Science and Information Technology, Universiti Malaya（马来亚大学计算机科学与信息学院） ； School of Computing and Information Systems, The University of Melbourne（墨尔本大学计算机与信息学院） 纠错

专题命中 医疗多模态 ：medical image(title,abstract)；MRI(abstract)；CT(abstract)；pathology(abstract)

Comments Accepted by IJCNN 2025, 8 pages, 8 figures, 3 tables

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

Sheng Zhang, Yanbo Xu, Naoto Usuyama, Hanwen Xu, Jaspreet Bagga, Robert Tinn, Sam Preston, Rajesh Rao, Mu Wei, Naveen Valluri, Cliff Wong, Andrea Tupini, Yu Wang, Matt Mazzola, Swadheen Shukla, Lars Liden, Jianfeng Gao, Angela Crabtree, Brian Piening, Carlo Bifulco, Matthew P. Lungren, Tristan Naumann, Sheng Wang, Hoifung Poon

专题命中 医疗多模态 ：biomedical(title,abstract)；medical AI(abstract)；medical image(abstract)；radiology(abstract)

Comments The models are released at https://aka.ms/biomedclip

DiagR1: A Vision-Language Model Trained via Reinforcement Learning for Digestive Pathology Diagnosis

Minxi Ouyang, Lianghui Zhu, Yaqing Bao, Qiang Huang, Jingli Ouyang, Tian Guan, Xitong Ling, Jiawen Li, Song Duan, Wenbin Dai, Li Zheng, Xuemei Zhang, Yonghong He

机构 * Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院） ； Department of Pathology, Liuzhou People’s Hospital Affiliated to Guangxi Medical University（广西医科大学柳州市人民医院病理科） ； Department of Immunology, College of Basic Medical Sciences, China Medical University（中国医科大学基础医学学院免疫科） ； Greater Bay Area Center for Medical Device Evaluation and Inspection.NMPA（粤港澳大湾区医疗器械评价和检验中心.NMPA） ； Shenzhen Shengqiang Technology Co., Ltd.（深圳盛强科技有限公司） ； Department of Pathology, Chongqing University Affiliated Three Gorges Hospital（重庆大学附属第三人民医院病理科） 纠错

专题命中 医疗多模态 ：pathology(title,abstract)；diagnosis(title)；分类 cs.CV、eess.IV

BiomedGPT: A Generalist Vision-Language Foundation Model for Diverse Biomedical Tasks

Kai Zhang, Rong Zhou, Eashan Adhikarla, Zhiling Yan, Yixin Liu, Jun Yu, Zhengliang Liu, Xun Chen, Brian D. Davison, Hui Ren, Jing Huang, Chen Chen, Yuyin Zhou, Sunyang Fu, Wei Liu, Tianming Liu, Xiang Li, Yong Chen, Lifang He, James Zou, Quanzheng Li, Hongfang Liu, Lichao Sun

专题命中 医疗多模态 ：biomedical(title,abstract)；medical AI(abstract)；diagnosis(abstract)；radiology(abstract)

Comments Fix incorrect citations and add journal reference for the published version. Nat Med (2024)

Multi-modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training

Jong Hak Moon, Hyungyung Lee, Woncheol Shin, Young-Hak Kim, Edward Choi

专题命中 医疗多模态 ：medical image(title,abstract)；diagnosis(abstract)；radiology(abstract)；biomedical(comments,journal_ref)

Comments Accepted by IEEE Journal of Biomedical and Health Informatics

Journal ref IEEE Journal of Biomedical and Health Informatics 2022

Scalable Training of Spatially Grounded 2D Vision-Language Models for Radiology

面向放射学的空间定位2D视觉-语言模型的可扩展训练

Yusuf Salcan, Simon Ging, Robin Tibor Schirrmeister, Philipp Arnold, Elmar Kotter, Behzad Bozorgtabar, Thomas Brox

机构 * Computer Vision Group, University of Freiburg, Germany（德国弗莱堡大学计算机视觉组） ； Department of Radiology, Medical Center -- University of Freiburg, Germany（德国弗莱堡大学医学中心放射科） ； CRIION-AI Lab, Freiburg, Germany（德国弗莱堡CRIION-AI实验室） 纠错

专题命中 医疗多模态 ：radiology(title,abstract)；CT(abstract,abstract_cn)；分类 cs.CV、cs.LG

AI总结 提出RefRad2D大规模双语数据集，通过LLM和自动分割生成空间定位数据，训练RadGrounder模型联合完成报告生成、VQA和空间定位，在外部基准上取得竞争性结果。

Comments Accepted for MICCAI 2026. First two authors: equal contribution. Last two authors: equal supervision

Reinforced Correlation Between Vision and Language for Precise Medical AI Assistant

Haonan Wang, Jiaji Mao, Lehan Wang, Qixiang Zhang, Marawan Elbatel, Yi Qin, Huijun Hu, Baoxun Li, Wenhui Deng, Weifeng Qin, Hongrui Li, Jialin Liang, Jun Shen, Xiaomeng Li

机构 * Department of Electronic and Computer Engineering, HKUST（香港科技大学电子与计算机工程系） ； Department of Radiology, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University（中山大学放射科、广东省恶性肿瘤表观遗传与基因调控重点实验室、中山纪念医院） ； Department of Computer Science and Engineering, HKUST（香港科技大学计算机科学与工程系） 纠错

专题命中 医疗多模态 ：medical AI(title,abstract)；medical image(abstract)；diagnosis(abstract)；分类 cs.CV、eess.IV

Bias-constrained multimodal intelligence for equitable and reliable clinical AI

具有偏见约束的多模态智能用于公平且可靠的临床AI

Cheng Li, Weijian Huang, Jiarun Liu, Hao Yang, Qi Yang, Song Wu, Ye Li, Hairong Zheng, Shanshan Wang

机构 * Paul C. Lauterbur Research Center for Biomedical Imaging（Paul C. Lauterbur生物医学成像研究中心） ； Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（深圳先进技术研究院，中国科学院） ； Pengcheng Laboratory（鹏城实验室） ； University of Chinese Academy of Sciences（中国科学院大学） ； Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University（首都医科大学北京朝阳医院放射科） ； Department of Urology, South China Hospital, Medical School, Shenzhen University（深圳大学南方医院泌尿科） ； Huawei Technologies Co., Ltd.（华为技术有限公司） 纠错

专题命中 医疗多模态 ：clinical AI(title)；pathology(abstract)；diagnosis(abstract)；radiology(abstract)

AI总结 本文提出BiasCareVL框架，通过在模型设计中直接引入偏见控制，解决医疗影像与文本整合中公平性和可靠性问题，展示了其在多任务和基准测试中的优越性能。

Beyond a Single Frame: Multi-Frame Spatially Grounded Reasoning Across Volumetric MRI

超越单帧：跨体积MRI的多帧空间接地推理

Lama Moukheiber, Caleb M. Yeung, Haotian Xue, Alec Helbling, Zelin Zhao, Yongxin Chen

机构 * Georgia Institute of Technology（佐治亚理工学院） ； Harvard University（哈佛大学） ； Georgetown University（乔治城大学） 纠错

专题命中 医疗多模态 ：MRI(title,title_cn)；分类 cs.CV

AI总结 本文提出SGMRI-VQA基准，通过多帧空间接地推理提升医学VLMs性能，展示监督微调提升接地能力。

Data-Efficient Fine-Tuning of Vision-Language Models for Diagnosis of Alzheimer's Disease

Fangqi Cheng, Surajit Ray, Xiaochen Yang

机构 * School of Mathematics and Statistics, University of Glasgow, UK（数学与统计学学院，格拉斯哥大学） 纠错

专题命中 医疗多模态 ：diagnosis(title,abstract)；MRI(abstract)；CT(abstract)；分类 cs.CV

Comments Accepted at MICAD 2025

Unifying Biomedical Vision-Language Expertise: Towards a Generalist Foundation Model via Multi-CLIP Knowledge Distillation

Shansong Wang, Zhecheng Jin, Mingzhe Hu, Mojtaba Safari, Feng Zhao, Chih-Wei Chang, Richard LJ Qiu, Justin Roper, David S. Yu, Xiaofeng Yang

机构 * Department of Radiation Oncology, Winship Cancer Institute, Emory University School of Medicine（放射肿瘤科，Winship癌症研究所，埃默里大学医学院） ； Department of Biomedical Engineering, College of Engineering, Georgia Institute of Technology（生物医学工程系，工程学院，佐治亚理工学院） ； Department of Computer Science and Mathematics, Laney Graduate School, Emory University（计算机科学与数学系，兰尼研究生院，埃默里大学） ； School of Electrical and Computer Engineering, College of Engineering, Georgia Institute of Technology（电气与计算机工程系，工程学院，佐治亚理工学院） 纠错

专题命中 医疗多模态 ：biomedical(title,abstract)；medical image(abstract)；diagnosis(abstract)；分类 cs.CV

RaDialog: A Large Vision-Language Model for Radiology Report Generation and Conversational Assistance

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, Nassir Navab, Matthias Keicher

机构 * Technical University of Munich（慕尼黑技术大学） 纠错

专题命中 医疗多模态 ：radiology(title,abstract)；medical image(abstract)；pathology(abstract)；分类 cs.CV

Comments Accepted for publication at MIDL 2025

E-MRL: Cross-view Aligned Evidence-driven Multimodal Reinforcement Learning for Reliable 3D Tumor Analysis

E-MRL: 跨视图对齐的证据驱动多模态强化学习用于可靠的3D肿瘤分析

Sijing Li, Zhongwei Qiu, Zhuoya Wang, Boxiang Yun, Zhenyu Yi, Jianwei Xu, Wenqiao Zhang, Yingda Xia, Ling Zhang

机构 * Zhejiang University（浙江大学） ； DAMO Academy, Alibaba Group（阿里巴巴集团达摩院） ； Hupan Lab（华平实验室） ； Huazhong University of Science and Technology（华中科技大学） ； East China Normal University（华东师范大学） ； Shanghai Jiao Tong University（上海交通大学） 纠错

专题命中 医疗多模态 ：CT(summary_cn,abstract)；diagnosis(abstract)；分类 cs.CV、eess.IV

AI总结 提出跨视图对齐的证据驱动多模态强化学习框架E-MRL，通过将生成过程建模为“诊断-定位-验证”的马尔可夫决策过程，并引入跨视图一致性奖励，减少视觉幻觉并提升3D CT肿瘤诊断准确性。

Comments 9 pages, 2 figures

A Multimodal Multi-Agent Framework for Radiology Report Generation

Ziruo Yi, Ting Xiao, Mark V. Albert

机构 * University of North Texas（北卡罗来纳州立大学） 纠错

专题命中 医疗多模态 ：radiology(title,abstract)；clinical AI(abstract)；medical image(abstract)

Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation

Ryutaro Tanno, David G. T. Barrett, Andrew Sellergren, Sumedh Ghaisas, Sumanth Dathathri, Abigail See, Johannes Welbl, Karan Singhal, Shekoofeh Azizi, Tao Tu, Mike Schaekermann, Rhys May, Roy Lee, SiWai Man, Zahra Ahmed, Sara Mahdavi, Yossi Matias, Joelle Barral, Ali Eslami, Danielle Belgrave, Vivek Natarajan, Shravya Shetty, Pushmeet Kohli, Po-Sen Huang, Alan Karthikesalingam, Ira Ktena

专题命中 医疗多模态 ：radiology(title,abstract)；diagnosis(abstract)；分类 cs.CV、cs.LG、eess.IV

Med-OPD: Improving Medical Vision-Language Models via Evidence-Aware On-Policy Distillation

Med-OPD：通过证据感知策略蒸馏改进医学视觉语言模型

Yunhang Qian, Jiaquan Yu, Jiawei Liu, Meng Wang, Hongwei Bran Li, Xiaobin Hu

机构 * National University of Singapore（新加坡国立大学） ； University of Science and Technology of China（中国科学技术大学） 纠错

专题命中 医疗多模态 ：MRI(abstract,abstract_cn)；CT(abstract,abstract_cn)；diagnosis(abstract)；分类 cs.CV

AI总结 研究针对医学视觉语言模型依赖语言先验而非视觉证据推理的问题，提出Med-OPD框架，引入医学证据优势信号，在令牌和轨迹级别重新分配蒸馏信号，实验证明该方法能加强模型对关键视觉证据的依赖，提升多模态医学推理能力。

The Scaffold Effect: How Prompt Framing Drives Apparent Multimodal Gains in Clinical VLM Evaluation

脚手架效应：提示框架如何驱动临床VLM评估中的表面多模态增益

Doan Nam Long Vu, Simone Balloccu

机构 * Technical University of Darmstadt（达姆施塔特技术大学） 纠错

专题命中 医疗多模态 ：MRI(summary_cn,abstract)；clinical AI(abstract)；分类 cs.LG

AI总结 研究发现，在临床VLM评估中，提示中提及MRI可用性即可解释70-80%的性能提升，与图像数据是否存在无关，这种“脚手架效应”揭示了表面评估无法反映真实多模态推理能力。

Scaling Large Vision-Language Models for Enhanced Multimodal Comprehension In Biomedical Image Analysis

Robinson Umeike, Neil Getty, Fangfang Xia, Rick Stevens

专题命中 医疗多模态 ：medical image(title)；biomedical(title)；分类 cs.CV

Comments 4 Pages, 4 Figures, 1 Table

Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis

Med3DVLM: 一种高效的视觉-语言模型用于3D医学图像分析

Yu Xin, Gorkem Can Ates, Kuang Gong, Wei Shao

机构 * University of Florida（佛罗里达大学） 纠错

专题命中 医疗多模态 ：medical image(title,abstract)；radiology(abstract)；分类 cs.CV、eess.IV

AI总结 Med3DVLM通过三个创新提出，实现了高效的3D医学图像分析，显著提升了图像-文本检索、报告生成和视觉问答的性能。

A Clinically-Grounded Two-Stage Framework for Renal CT Report Generation

Renjie Liang, Zhengkang Fan, Jinqian Pan, Chenkun Sun, Bruce Daniel Steinberg, Russell Terry, Jie Xu

机构 * Department of Health Outcomes and Biomedical Informatics, University of Florida（健康结果与生物医学信息学系，佛罗里达大学） ； Department of Urology, University of Florida（泌尿外科系，佛罗里达大学） 纠错

专题命中 医疗多模态 ：CT(title,abstract)；medical AI(abstract)；分类 cs.CV、eess.IV

Effectively Fine-tune to Improve Large Multimodal Models for Radiology Report Generation

Yuzhe Lu, Sungmin Hong, Yash Shah, Panpan Xu

专题命中 医疗多模态 ：radiology(title,abstract)；medical image(abstract)；分类 cs.CV、cs.LG

Comments Accepted to Deep Generative Models for Health Workshop at NeurIPS 2023

A Self-Guided Framework for Radiology Report Generation

Jun Li, Shibo Li, Ying Hu, Huiren Tao

专题命中 医疗多模态 ：radiology(title,abstract)；diagnosis(abstract)；分类 cs.CV；medical image(comments)

Comments 11 pages, 3 figures, accepted by Medical Image Computing and Computer Assisted Intervention 2022(MICCAI 2022)

Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation

Changsun Lee, Sangjoon Park, Cheong-Il Shin, Woo Hee Choi, Hyun Jeong Park, Jeong Eun Lee, Jong Chul Ye

专题命中 医疗多模态 ：medical image(abstract)；MRI(abstract)；CT(abstract)；radiology(abstract)

Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning

Evi-Steer：通过高效且可泛化的证据调优学习引导生物医学视觉-语言模型

Taha Koleilat, Hassan Rivaz, Yiming Xiao

机构 * Concordia University（康科迪亚大学） 纠错

专题命中 医疗多模态 ：biomedical(title,abstract)；medical image(abstract)；分类 cs.CV

AI总结 提出Evi-Steer框架，通过证据跨模态低维引导实现BiomedCLIP的不确定性感知参数高效微调，仅更新0.11%参数，在15个生物医学数据集上少样本学习和域泛化设置中优于现有方法。

Comments MICCAI 2026 Early Accept; Project Page: https://tahakoleilat.github.io/Evi-Steer. This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution will be published as part of the MICCAI 2026 proceedings in October

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering

用于胃肠内窥镜的参数高效视觉语言模型：医学图像生成与临床视觉问答

Ojonugwa Oluwafemi Ejiga Peter, Frederick Akor Ejiga, Fahmi Khalifa, Md Mahmudur Rahman

机构 * Computer Science Department, Morgan State University（莫尔甘州大学计算机科学系） ； International Organization for Migration (IOM)（国际移民组织） ； Electrical & Computer Engineering Department, Morgan State University（莫尔甘州大学电气与计算机工程系） 纠错

专题命中 医疗多模态 ：medical image(title)；clinical AI(abstract)；diagnosis(abstract)；分类 cs.CV

AI总结 提出双流水线参数高效微调模型，结合Florence-2和LoRA Stable Diffusion，分别解决临床视觉问答和隐私保护合成数据生成问题，在Kvasir-VQA数据集上取得高ROUGE和BLEU分数，并显著降低计算成本。

MedMO: Grounding and Understanding Multimodal Large Language Model for Medical Images

MedMO：为医学图像构建和理解多模态大语言模型

Ankan Deria, Komal Kumar, Adinath Madhavrao Dukre, Eran Segal, Salman Khan, Imran Razzak

专题命中 医疗多模态 ：medical image(title)；pathology(abstract)；radiology(abstract)；分类 cs.CV

AI总结 MedMO是一种基于通用MLLM架构构建的医学多模态基础模型，通过多阶段训练提升跨模态和任务的性能，超越现有开源基线，在医学图像识别和报告生成中取得显著提升。

Comments 21 pages, 6 figures and 4 tables

HyperWalker: Dynamic Hypergraph-Based Deep Diagnosis for Multi-Hop Clinical Modeling across EHR and X-Ray in Medical VLMs

HyperWalker: 基于动态超图的多跳临床建模深度诊断方法，跨EHR和X光在医学视觉语言模型中

Yuezhe Yang, Hao Wang, Yige Peng, Jinman Kim, Lei Bi

机构 * Institute of Translational Medicine, Shanghai Jiao Tong University（翻译医学研究院，上海交通大学） ； School of Computer Science, University of Sydney（计算机科学学院，悉尼大学） 纠错

专题命中 医疗多模态 ：diagnosis(title,abstract)；medical AI(abstract)；分类 cs.CV

AI总结 HyperWalker通过动态超图和测试时训练，实现跨EHR和X光的多跳临床建模深度诊断，提升医疗视觉语言模型的诊断性能。

Comments Under Review