多模态信息融合

UniDCF: A Foundation Model for Comprehensive Dentocraniofacial Hard Tissue Reconstruction

Chunxia Ren, Ning Zhu, Yue Lai, Gui Chen, Ruijie Wang, Yangyi Hu, Suyao Liu, Shuwen Mao, Hong Su, Yu Zhang, Li Xiao

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

Comments 23 pages, 6 figures

Memory-Augmented Incomplete Multimodal Survival Prediction via Cross-Slide and Gene-Attentive Hypergraph Learning

Mingcheng Qu, Guang Yang, Donglin Di, Yue Gao, Tonghua Su, Yang Song, Lei Fan

机构 * Faculty of Computing, Harbin Institute of Technology（哈尔滨工业大学计算机学院） ； School of Software, Tsinghua University（清华大学软件学院） ； School of Computer Science and Engineering, UNSW Sydney（新南威尔士大学计算机科学与工程学院） 纠错

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

Comments accepted by MICCAI2025 code: https://github.com/MCPathology/M2Surv

BrainMAP: Multimodal Graph Learning For Efficient Brain Disease Localization

Nguyen Linh Dan Le, Jing Ren, Ciyuan Peng, Chengyao Xie, Bowen Li, Feng Xia

机构 * School of Computing Technologies, RMIT University（计算技术学院，拉筹纳斯大学） ； Institute of Innovation, Science and Sustainability, Federation University Australia（创新、科学与可持续性研究所，联邦大学澳大利亚） 纠错

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

Comments 6 pages, 5 figures

Cross-Sequence Semi-Supervised Learning for Multi-Parametric MRI-Based Visual Pathway Delineation

Alou Diakite, Cheng Li, Lei Xie, Yuanjing Feng, Ruoyou Wu, Jianzhong He, Hairong Zheng, Shanshan Wang

机构 * Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（生物医学成像保罗·C·劳特伯研究中心，深圳先进技术研究所，中国科学院） ； University of Chinese Academy of Sciences（中国科学院大学） 纠错

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

Improving Colorectal Cancer Screening and Risk Assessment through Predictive Modeling on Medical Images and Records

Shuai Jiang, Christina Robinson, Joseph Anderson, William Hisey, Lynn Butterly, Arief Suriawinata, Saeed Hassanpour

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

Distilled Prompt Learning for Incomplete Multimodal Survival Prediction

Yingxue Xu, Fengtao Zhou, Chenyu Zhao, Yihui Wang, Can Yang, Hao Chen

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

Comments Accepted by CVPR2025

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