多模态信息融合

MMLNB: Multi-Modal Learning for Neuroblastoma Subtyping Classification Assisted with Textual Description Generation

Huangwei Chen, Yifei Chen, Zhenyu Yan, Mingyang Ding, Chenlei Li, Zhu Zhu, Feiwei Qin

专题命中 医学影像融合 ：multi-modal fusion(abstract)；分类 cs.CV

Comments 25 pages, 7 figures

GFE-Mamba: Mamba-based AD Multi-modal Progression Assessment via Generative Feature Extraction from MCI

Zhaojie Fang, Shenghao Zhu, Yifei Chen, Binfeng Zou, Fan Jia, Chang Liu, Xiang Feng, Linwei Qiu, Feiwei Qin, Jin Fan, Changbiao Chu, Changmiao Wang

专题命中 医学影像融合 ：multimodal fusion(abstract)；分类 cs.CV

Comments 13 pages, 9 figures

Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI

Lucas W. Remedios, Han Liu, Samuel W. Remedios, Lianrui Zuo, Adam M. Saunders, Shunxing Bao, Yuankai Huo, Alvin C. Powers, John Virostko, Bennett A. Landman

专题命中 医学影像融合 ：multimodal fusion(abstract)；分类 cs.CV

Comments 13.5 pages of manuscript content

Weakly supervised alignment and registration of MR-CT for cervical cancer radiotherapy

Jjahao Zhang, Yin Gu, Deyu Sun, Yuhua Gao, Ming Gao, Ming Cui, Teng Zhang, He Ma

专题命中 医学影像融合 ：information fusion(abstract)；分类 cs.CV

Self-Supervised Modality-Agnostic Pre-Training of Swin Transformers

Abhiroop Talasila, Maitreya Maity, U. Deva Priyakumar

专题命中 医学影像融合 ：multi-modal fusion(abstract)；分类 cs.CV

FedMM: Federated Multi-Modal Learning with Modality Heterogeneity in Computational Pathology

Yuanzhe Peng, Jieming Bian, Jie Xu

专题命中 医学影像融合 ：multimodal fusion(abstract)；分类 cs.CV

Journal ref 2024 International Conference on Acoustics, Speech and Signal Processing (ICASSP 2024)

Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection

Pramit Saha, Divyanshu Mishra, Felix Wagner, Konstantinos Kamnitsas, J. Alison Noble

专题命中 医学影像融合 ：information fusion(abstract)；分类 cs.CV

Comments 42 pages

Diagnosing Alzheimer's Disease using Early-Late Multimodal Data Fusion with Jacobian Maps

Yasmine Mustafa, Tie Luo

专题命中 医学影像融合 ：multimodal fusion(abstract)；分类 cs.CV

Comments To be published in Proceedings of 2023 IEEE Healthcom, December 2023

Adaptive De-noising of Photoacoustic Signal and Image based on Modified Kalman Filter

Tianqu Hu, Zihao Huang, Peng Ge, Feng Gao, Fei Gao

专题命中 医学影像融合 ：hybrid fusion(abstract)；分类 eess.SP

An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI

Yifan Gao, Yin Dai, Fayu Liu, Weibing Chen, Lifu Shi

专题命中 医学影像融合 ：multimodal fusion(abstract)；分类 eess.IV

Comments under review

Image-guided Breast Biopsy of MRI-visible Lesions with a Hand-mounted Motorised Needle Steering Tool

Marta Lagomarsino, Vincent Groenhuis, Maura Casadio, Marcel K. Welleweerd, Francoise J. Siepel, Stefano Stramigioli

专题命中 医学影像融合 ：image fusion(abstract)；分类 cs.RO

Comments Submitted to 2021 International Symposium on Medical Robotics (ISMR)

Learning Deformable Image Registration from Optimization: Perspective, Modules, Bilevel Training and Beyond

Risheng Liu, Zi Li, Xin Fan, Chenying Zhao, Hao Huang, Zhongxuan Luo

专题命中 医学影像融合 ：multi-modal fusion(abstract)；分类 cs.CV

Journal ref IEEE Transactions on Pattern Analysis and Machine Intelligence 2021

Co-Learning Feature Fusion Maps from PET-CT Images of Lung Cancer

Ashnil Kumar, Michael Fulham, Dagan Feng, Jinman Kim

专题命中 医学影像融合 ：image fusion(abstract)；分类 cs.CV

Comments Source code is available from https://github.com/ashnilkumar/colearn . The paper has been accepted for publication in IEEE Transactions on Medical Imaging. The final published version of the manuscript can be accessed from the IEEE. The paper contains 21 pages (14 main paper, 7 supplementary), 16 images (8 main paper, 8 supplementary), and 3 tables

Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging

Qingjie Meng, Matthew Sinclair, Veronika Zimmer, Benjamin Hou, Martin Rajchl, Nicolas Toussaint, Ozan Oktay, Jo Schlemper, Alberto Gomez, James Housden, Jacqueline Matthew, Daniel Rueckert, Julia Schnabel, Bernhard Kainz

专题命中 医学影像融合 ：image fusion(abstract)；分类 cs.CV

IVD-Net: Intervertebral disc localization and segmentation in MRI with a multi-modal UNet

Jose Dolz, Christian Desrosiers, Ismail Ben Ayed

专题命中 医学影像融合 ：multi-modal fusion(abstract)；分类 cs.CV

Comments Manuscript submitted to the Proceedings of the MICCAI 2018 IVD Challenge. arXiv admin note: text overlap with arXiv:1810.07003

Deep Learning based Inter-Modality Image Registration Supervised by Intra-Modality Similarity

Xiaohuan Cao, Jianhua Yang, Li Wang, Zhong Xue, Qian Wang, Dinggang Shen

专题命中 医学影像融合 ：information fusion(abstract)；分类 cs.CV

Comments 8 pages, 4 figures

A Segmentation-aware Deep Fusion Network for Compressed Sensing MRI

Zhiwen Fan, Liyan Sun, Xinghao Ding, Yue Huang, Congbo Cai, John Paisley

专题命中 医学影像融合 ：information fusion(abstract)；分类 cs.CV

Elastic LiDAR Fusion: Dense Map-Centric Continuous-Time SLAM

Chanoh Park, Peyman Moghadam, Soohwan Kim, Alberto Elfes, Clinton Fookes, Sridha Sridharan

专题命中 医学影像融合 ：sensor fusion(abstract)；分类 cs.RO

Comments 8 pages, accepted to ICRA 2018 Demo video link: https://www.youtube.com/watch?v=QNNLncT9XmQ

MambaEviScrib: Mamba and Evidence-Guided Consistency Enhance CNN Robustness for Scribble-Based Weakly Supervised Ultrasound Image Segmentation

Xiaoxiang Han, Xinyu Li, Jiang Shang, Yiman Liu, Keyan Chen, Shugong Xu, Qiaohong Liu, Qi Zhang

机构 * School of Communication and Information Engineering, Shanghai University（上海大学通信与信息工程学院） ； The SMART (Smart Medicine and AI-based Radiology Technology) Lab, Shanghai Institute for Advanced Communication and Data Science, Shanghai University（上海大学先进通信与数据科学研究院智能医学与AI放射技术实验室） ； School of Health Science and Engineering, University of Shanghai for Science and Technology（上海科技大学健康科学与工程学院） ； Department of Pediatric Cardiology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院儿童心脏科部） ； School of Medical Instruments, Shanghai University of Medicine and Health Sciences（医学仪器学院，上海医学院与健康科学大学） 纠错

专题命中 医学影像融合 ：information fusion(comments,journal_ref)；分类 cs.CV、eess.IV

Comments Accepted by Information Fusion

Journal ref Information Fusion 126 (2026) 103590

Fusion is not one-size-fits-all: Cross-Modal Representation Alignment for Time-to-Event Modeling

融合并非一刀切：用于时间-事件建模的跨模态表示对齐

Zhemin Zhang, Weijie Chen, David Le, Amara Tariq, Alex Wallace, Matthew Stib, Juan Maria Farina, Chadi Ayoub, Reza Arsanjani, Imon Banerjee

机构 * Arizona State University（亚利桑那州立大学） ； Mayo Clinic（梅奥诊所） 纠错

专题命中 医学影像融合 ：multimodal fusion(abstract)

AI总结 针对多模态临床数据中的模态不平衡和分布偏移问题，提出一种基于基础模型的跨模态对齐框架，通过四种融合策略在CT影像和纵向EHR数据间进行表示对齐，在肺栓塞死亡率和心血管疾病结局预测任务上验证了融合的有效性，并首次系统分析了时间-事件预测中的模态不平衡对融合行为的影响。

The Role of Free-breathing GRASP MRI in Accurate Phase Matching with 4D-CT for Motion Representation in Liver Cancer Radiotherapy

自由呼吸GRASP MRI在肝癌放疗中与4D-CT精确相位匹配以表征运动中的作用

Junchao Li, Shengqi Chen, Guohua Wu, Jianrong Dai, Jiayun Chen, Fei Liu

专题命中 医学影像融合 ：image fusion(abstract)

AI总结 研究自由呼吸GRASP MRI能否代表肝癌立体定向放疗中的呼吸运动，发现其仅在30%-60%呼吸相位（最佳50%）准确表征运动，需结合4D-CT或动态成像。

Comments 25 pages, 4 figures

Tensor Analysis and Fusion of Multimodal Brain Images

张量分析与多模态脑图像融合

Esin Karahan, Pedro A. Rojas-Lopez, Maria L. Bringas-Vega, Pedro A. Valdes-Hernandez, Pedro A. Valdes-Sosa

专题命中 医学影像融合 ：multimodal fusion(abstract)

AI总结 本文提出利用张量结构分析多模态神经影像数据，引入马尔可夫-彭罗斯图进行建模，首次将Granger因果分析视为张量回归问题，展示其在脑网络分解中的潜力。

Comments 23 pages, 15 figures, submitted to Proceedings of the IEEE

Multimodal Cancer Modeling in the Age of Foundation Model Embeddings

多模态癌症建模：在基础模型嵌入时代

Steven Song, Morgan Borjigin-Wang, Irene Madejski, Robert L. Grossman

机构 * Center for Translational Data Science（转化数据科学中心） ； Department of Computer Science（计算机科学系） ； University of Chicago（芝加哥大学） ； Medical Scientist Training Program（医学科学家培训计划） ； Brown University（布朗大学） ； Section of Biomedical Data Science（生物医学数据科学部门） ； Department of Medicine（医学系） 纠错

专题命中 医学影像融合 ：multimodal fusion(abstract)

AI总结 本文探讨了利用基础模型嵌入进行多模态癌症建模的可能性，展示了多模态融合的优势，并评估了病理报告文本和文本摘要对模型性能的影响。

Comments camera ready version for ML4H 2025, typo corrected

Journal ref Proceedings of the Fifth Machine Learning for Health Symposium, PMLR 297:202-227, 2026

Toward Personalized Digital Twins for Cognitive Decline Assessment: A Multimodal, Uncertainty-Aware Framework

迈向认知下降评估的个性化数字孪生：一种多模态、不确定性感知的框架

Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang, Laura J. Brattain

机构 * Department of Mechanical, Industrial \& Manufac. Eng. The University of Toledo Toledo, OH, USA ； Department of Industrial Eng. ； Mngt. Systems University of Central Florida Orlando, FL, USA ； Department of Statistics ； Data Science University of Central Florida Orlando, FL, USA ； Department of Internal Medicine University of Central Florida Orlando, FL, USA 纠错

专题命中 医学影像融合 ：multimodal fusion(abstract)

AI总结 本文提出了一种多模态、不确定性感知的框架，用于从稀疏、噪声和不规则的纵向数据中建模患者特定的疾病轨迹，通过结合潜在状态空间模型、多模态融合和不确定性感知验证，实现对认知下降的个性化评估。

Comments 6 pages, 6 figures

Detecting Neurovascular Instability from Multimodal Physiological Signals Using Wearable-Compatible Edge AI: A Responsible Computational Framework

通过可穿戴设备的边缘AI检测神经血管不稳定性：一种负责任的计算框架

Truong Quynh Hoa, Hoang Dinh Cuong, Truong Xuan Khanh

机构 * H&K Research Studio, Clevix LLC（H&K研究室，Clevix LLC） ； Department of Cardiology, Hanoi Heart Hospital（心血管科，河内心脏医院） 纠错

专题命中 医学影像融合 ：multimodal fusion(abstract)

AI总结 本文提出Melaguard框架，通过融合多种生理信号检测神经血管不稳定性，优于单一模态设备，通过三阶段验证提升检测性能。

Comments 11 pages, 8 figures, 6 tables. Submitted to IEEE JBHI. Code: https://github.com/ClevixLab/Melaguard

Multimodal normative modeling in Alzheimers Disease with introspective variational autoencoders

在阿尔茨海默病中使用反思变分自编码器的多模态规范建模

Sayantan Kumar, Peijie Qiu, Aristeidis Sotiras

机构 * Washington University in St Louis（华盛顿大学圣路易斯分校） ； Washington University in St Louis School of Medicine（华盛顿大学圣路易斯医学院） 纠错

专题命中 医学影像融合 ：multimodal fusion(abstract)

AI总结 本文提出mmSIVAE，通过结合MOPOE聚合提升多模态数据的规范建模效果，提高参考分布保真度和多模态整合能力，用于阿尔茨海默病的偏差分析。

Comments Conference on Health, Inference, and Learning (CHIL)

Multimodal Deep Learning for Prediction of Progression-Free Survival in Patients with Neuroendocrine Tumors Undergoing 177Lu-based Peptide Receptor Radionuclide Therapy

Simon Baur, Tristan Ruhwedel, Ekin Böke, Zuzanna Kobus, Gergana Lishkova, Christoph Wetz, Holger Amthauer, Christoph Roderburg, Frank Tacke, Julian M. Rogasch, Wojciech Samek, Henning Jann, Jackie Ma, Johannes Eschrich

机构 * Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute（人工智能部门，弗劳恩霍夫海因里希·赫兹研究所） ； Department of Nuclear Medicine, Charité—Universitätsmedizin Berlin（核医学部门，柏林查理医院） ； Department of Hepatology and Gastroenterology, Charité—Universitätsmedizin Berlin（肝病与胃肠病学部门，柏林查理医院） ； Division of Interventional Radiology, Department of Radiology, Memorial Sloan Kettering Cancer Center（介入放射学部门，纪念斯隆-凯特琳癌症中心） ； Department of Endocrinology and Metabolism, Charité—Universitätsmedizin Berlin（内分泌与代谢学部门，柏林查理医院） ； Clinic for Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Medical Faculty of Heinrich Heine University Düsseldorf（胃肠病、肝病和传染病诊所，杜塞尔多夫大学医院，海因里希·海涅大学医学部） ； Department of Electrical Engineering and Computer Science, Technische Universität Berlin（电气工程与计算机科学部门，柏林技术大学） ； Berlin Institute of Health at Charité – Universitätsmedizin Berlin（柏林查理医院健康研究所） 纠错

专题命中 医学影像融合 ：multimodal fusion(abstract)

HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models

Aakash Tripathi, Asim Waqas, Matthew B. Schabath, Yasin Yilmaz, Ghulam Rasool

专题命中 医学影像融合 ：multimodal fusion(abstract)

One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data

Michal Golovanevsky, Eva Schiller, Akira Nair, Eric Han, Ritambhara Singh, Carsten Eickhoff

专题命中 医学影像融合 ：information fusion(abstract)

Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis

Zeyu Zhang, Yuanshen Zhao, Jingxian Duan, Yaou Liu, Hairong Zheng, Dong Liang, Zhenyu Zhang, Zhi-Cheng Li

专题命中 医学影像融合 ：multi-modal fusion(abstract)