医学 AI

SlicerPET: A workflow based software module for PET/CT guided needle biopsy

Dženan Zukić, Julien Finet, Emmanuel Wilson, Filip Banovac, Giuseppe Esposito, Kevin Cleary, Andinet Enquobahrie

专题命中 医学影像 ：CT(title,abstract)；diagnosis(abstract)

Monte Carlo-based Noise Compensation in Coil Intensity Corrected Endorectal MRI

Dorothy Lui, Amen Modhafar, Masoom Haider, Alexander Wong

专题命中 医学影像 ：MRI(title,abstract)；diagnosis(abstract)

Comments 23 pages

Development of an Electronic Medical Image Archiving System for Health Care in Nigeria

Mikail Olaniyi, Adebayo Omotosho, Jane Robert, Alice Oke

专题命中 医学影像 ：medical image(title,abstract)；diagnosis(abstract)

Journal ref International Journal of Computer and Information Technology,Volume 02, Issue 04, 2013 p.706-711

Hardware-Accelerated Raycasting: Towards an Effective Brain MRI Visualization

A. M. Adeshina, R. Hashim, N. E. A. Khalid, Siti Z. Z. Abidin

专题命中 医学影像 ：MRI(title,abstract)；diagnosis(abstract)

Comments Journal of Computing, Volume 3, Issue 10, October 2011, ISSN 2151-9617

Medical Image Denoising using Adaptive Threshold Based on Contourlet Transform

S. Satheesh, KVSVR Prasad

专题命中 医学影像 ：medical image(title,abstract)；MRI(abstract)

Comments 7 pages, 6 figures,Advanced Computing: An International Journal (ACIJ) ISSN: 2229 - 6727 [Online]; 2229 - 726X [Print]

Microtesla MRI with dynamic nuclear polarization

V. S. Zotev, T. Owens, A. N. Matlashov, I. M. Savukov, J. J. Gomez, M. A. Espy

专题命中 医学影像 ：MRI(title,abstract)；biomedical(abstract)

Comments 14 pages, 10 figures

Journal ref J.Magn.Resonance 207:78-88, 2010

Energetics in MRI driven Turbulence

Thomas A. Gardiner, James M. Stone

专题命中 医学影像 ：MRI(title,abstract)；CT(abstract)

Comments 14 pages, Conference Proceedings: "Magnetic Fields in the Universe: from Laboratory and Stars to Primordial Structures"

Prospective Study for Semantic Inter-Media Fusion in Content-Based Medical Image Retrieval

Roxana Teodorescu, Daniel Racoceanu, Wee-Kheng Leow, Vladimir Cretu

专题命中 医学影像 ：medical image(title,abstract)；pathology(abstract)

Comments 11 pages

Tree-NET: Enhancing 2D Medical Image Segmentation Through Efficient Low-Level Feature Training

Tree-NET：通过高效低级特征训练增强二维医学图像分割

Orhan Demirci, Bulent Yilmaz

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.IV

AI总结 本文提出新型医学图像分割框架Tree-NET，采用双瓶颈监督的三组件架构，可降低计算开销，在皮肤病变、息肉分割任务上提升效率且保持精度，表现优于或匹配基线模型。

Comments This manuscript is 24 pages long, includes 10 figures and 4 tables, and presents a novel framework for medical image segmentation. It has been accepted from Neural Computing and Applications journal

Unsupervised Adaptation from FDG to PSMA PET/CT for 3D Lesion Detection under Label Shift

从FDG到PSMA PET/CT的无监督适应用于在标签偏移下的3D病灶检测

Xiaofeng Liu, Menghua Xia, Yanis Chemli, Georges El Fakhri, Chi Liu, Jinsong Ouyang

机构 * Yale Biomedical Imaging Institute and Department of Radiology & Biomedical Imaging, Yale University（耶鲁生物医学成像研究所和放射学与生物医学成像系，耶鲁大学） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

AI总结 本文提出一种无监督领域适应框架，用于将训练于FDG PET/CT上的检测器适应到未标记的PSMA PET/CT，通过自训练机制应对标签偏移问题，提升跨示踪检测的鲁棒性。

Comments IEEE International Symposium on Biomedical Imaging (ISBI) 2026

Attention-Enhanced U-Net for Accurate Segmentation of COVID-19 Infected Lung Regions in CT Scans

注意力增强的U-Net用于准确分割CT扫描中感染的肺部区域

Amal Lahchim, Lazar Davic

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV

AI总结 本文提出一种结合注意力机制的改进U-Net模型，用于提高CT扫描中新冠肺部感染区域分割的准确性，实验结果显示其在Dice系数和IoU指标上均优于其他方法。

Comments 14 pages, 9 figures, created using Google Colab and PyTorch. Compares segmentation models for COVID-19 CT data

Vision-Language Controlled Deep Unfolding for Joint Medical Image Restoration and Segmentation

视觉-语言控制的深度展开用于联合医学图像恢复与分割

Ping Chen, Zicheng Huang, Xiangming Wang, Yungeng Liu, Bingyu Liang, Haijin Zeng, Yongyong Chen

机构 * Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳）） ； Harvard University（哈佛大学） ； SUN YAT-SEN UNIVERSITY（中山大学） 纠错

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.IV

AI总结 VL-DUN通过联合优化和频率感知Mamba机制，实现医学图像恢复与分割的协同学习，提升PSNR和Dice系数，展示联合学习在复杂临床任务中的优势。

Comments 18 pages, medical image

Bonnet: Ultra-fast whole-body bone segmentation from CT scans

Bonnet: 从CT扫描中快速完成全身骨骼分割

Hanjiang Zhu, Pedro Martelleto Rezende, Zhang Yang, Tong Ye, Bruce Z. Gao, Feng Luo, Siyu Huang, Jiancheng Yang

机构 * ELLIS Institute Finland（埃利斯研究所芬兰分校） ； Aalto University（艾尔沃斯大学） ； Clemson University（克莱姆森大学） ； ETH Zurich（苏黎世联邦理工学院） ； Fujian Medical University Union Hospital（福建省医科大学附属医院） ； Fujian Medical University（福建省医科大学） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

AI总结 Bonnet通过高效算法在2.69秒内实现全身骨骼分割，准确度高且速度快。

Comments 5 pages, 2 figures. Accepted for publication at the 2026 IEEE International Symposium on Biomedical Imaging (ISBI 2026)

MedPrompt: LLM-CNN Fusion with Weight Routing for Medical Image Segmentation and Classification

MedPrompt: 基于权重路由的LLM-CNN融合用于医学图像分割与分类

Shadman Sobhan, Kazi Abrar Mahmud, Abduz Zami

机构 * 1 ,2 Department of Electrical ； Electronic Engineering,\ University of Engineering ； 3Department of Computer Science \& Engineering,\ University of Engineering \& Technology, Rajshahi-6204, Bangladesh 纠错

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.SP；biomedical(journal_ref)

AI总结 MedPrompt结合LLM和CNN实现医学图像分割与分类，通过权重路由提高可扩展性，实现高准确率和低延迟的实时应用。

Comments 40 pages, 8 Tables, 9 Figures

Journal ref Published at Biomedical Signal Processing and Control Volume 113, Part D, March 2026, 109251

Patch-Based Diffusion for Data-Efficient, Radiologist-Preferred MRI Reconstruction

基于补丁的扩散模型用于数据高效、放射科医师偏好的MRI重建

Rohan Sanda, Asad Aali, Andrew Johnston, Eduardo Reis, Gordon Wetzstein, Sara Fridovich-Keil

机构 * Stanford University（斯坦福大学） ； Stanford University School of Medicine（斯坦福大学医学院） ； Stanford Center for Artificial Intelligence in Medicine and Imaging（斯坦福大学医学与成像人工智能中心） ； Georgia Institute of Technology（佐治亚理工学院） 纠错

专题命中 医学影像 ：MRI(title,abstract)；分类 cs.CV、eess.IV

AI总结 本文提出基于补丁的扩散模型用于高效MRI重建，在小数据集上表现优于现有方法，且被放射科医师认为诊断效果更优。

Comments Code is available at: https://github.com/voilalab/PaDIS-MRI

Learning accurate rigid registration for longitudinal brain MRI from synthetic data

从合成数据中学习准确的纵向脑部MRI刚体配准

Jingru Fu, Adrian V. Dalca, Bruce Fischl, Rodrigo Moreno, Malte Hoffmann

机构 * 1 Division of Biomedical Imaging, KTH Royal Institute of Technology, Huddinge, Sweden 2 Athinoula A.\ Martinos Center for Biomedical Imaging, Charlestown, USA 3 Department of Radiology, Massachusetts General Hospital, Boston, USA 4 Department of Radiology, Harvard Medical School, Boston, USA 5 Computer Science \& Artificial Intelligence Laboratory, MIT, Cambridge, USA 纠错

专题命中 医学影像 ：MRI(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

AI总结 本文提出了一种基于合成数据训练的模型，用于提高纵向脑部MRI刚体配准的准确性。

Comments 5 pages, 4 figures, 1 table, rigid image registration, deep learning, longitudinal analysis, neuroimaging, accepted by the IEEE International Symposium on Biomedical Imaging

Journal ref IEEE Int Symp Biomed Imaging, 2025, 1-5

Disentangling Progress in Medical Image Registration: Beyond Trend-Driven Architectures towards Domain-Specific Strategies

解构医学图像配准的进步：超越趋势驱动的架构，迈向领域特定的策略

Bailiang Jian, Jiazhen Pan, Rohit Jena, Morteza Ghahremani, Hongwei Bran Li, Daniel Rueckert, Christian Wachinger, Benedikt Wiestler

机构 * Technical University of Munich（慕尼黑技术大学） ； Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心） ； Imperial College London（伦敦帝国理工学院） ； University of Pennsylvania（宾夕法尼亚大学） ； National University of Singapore（新加坡国立大学） 纠错

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.IV

AI总结 本文通过模块化框架解构医学图像配准中趋势驱动架构与领域特定设计的影响，发现后者在性能提升上优于前者，推动研究重点转向领域特定原则。

Comments Submitted to Medical Image Analysis. Journal Extension of arXiv:2407.19274

Generalist Models in Medical Image Segmentation: A Survey and Performance Comparison with Task-Specific Approaches

通用模型在医学图像分割中的应用：一项调查与与任务特定方法的性能比较

Andrea Moglia, Matteo Leccardi, Matteo Cavicchioli, Alice Maccarini, Marco Marcon, Luca Mainardi, Pietro Cerveri

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.IV

AI总结 本文调查了通用模型在医学图像分割中的应用，对比了通用模型与任务特定方法的性能，探讨了其在监管、隐私、预算及临床转化等方面面临的挑战。

Comments 132 pages, 26 figures, 23 tables. Andrea Moglia and Matteo Leccardi are equally contributing authors

Journal ref Moglia A, et al.Generalist models in medical image segmentation: A survey and performance comparison with task-specific approaches. Inf Fus 2026 https://www.sciencedirect.com/science/article/pii/S156625352500781X

BreastSegNet: Multi-label Segmentation of Breast MRI

Qihang Li, Jichen Yang, Yaqian Chen, Yuwen Chen, Hanxue Gu, Lars J. Grimm, Maciej A. Mazurowski

机构 * Department of Biostatistics \& Bioinformatics, Duke University Department of Electrical ； Computer Engineering, Duke University Department of Radiology, Duke University Medical Center Department of Computer Science, Duke University 纠错

专题命中 医学影像 ：MRI(title,abstract)；分类 cs.CV、eess.IV；medical image(journal_ref)

Journal ref Medical Image Computing and Computer Assisted Intervention, MICCAI, 2025

PoCGM: Poisson-Conditioned Generative Model for Sparse-View CT Reconstruction

Changsheng Fang, Yongtong Liu, Bahareh Morovati, Shuo Han, Li Zhou, Hengyong Yu

机构 * Department of Electrical and Computer Engineering, University of Massachusetts Lowel（电气与计算机工程系，马萨诸塞大学洛伊尔分校） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；radiology(comments)

Comments 18th International Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine, Shanghai, CHINA, 2025

Self-Supervised Training For Low Dose CT Reconstruction

Mehmet Ozan Unal, Metin Ertas, Isa Yildirim

机构 * Electronics and Communication Engineering Department, Istanbul Technical University, Istanbul, Turkey（电子与通信工程系，伊斯坦布尔技术大学） ； Electrical and Electronics Engineering Department, Istanbul University, Istanbul, Turkey（电气与电子工程系，伊斯坦布尔大学） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；biomedical(journal_ref)

Journal ref 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)

MedVKAN: Efficient Feature Extraction with Mamba and KAN for Medical Image Segmentation

Hancan Zhu, Jinhao Chen, Guanghua He

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

Comments This preprint has been published in Biomedical Signal Processing and Control, Volume 112, 2026, Article 108821

Interpretability-Aware Pruning for Efficient Medical Image Analysis

Nikita Malik, Pratinav Seth, Neeraj Kumar Singh, Chintan Chitroda, Vinay Kumar Sankarapu

机构 * AryaXAI Alignment Lab, AryaXAI.com, Mumbai, India（AryaXAI对齐实验室） ； Manipal Institute of Technology, Manipal, India（曼尼帕尔理工学院） 纠错

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、cs.LG；medical AI(comments)

Comments Accepted at The 1st MICCAI Workshop on Efficient Medical AI 2025

Evaluation of Machine Learning Reconstruction Techniques for Accelerated Brain MRI Scans

Jonathan I. Mandel, Shivaprakash Hiremath, Hedyeh Keshtgar, Timothy Scholl, Sadegh Raeisi

专题命中 医学影像 ：MRI(title,abstract)；分类 cs.CV、eess.IV；radiology(comments)

Comments This work has been submitted to Radiology: Artificial Intelligence for possible publication

State of Abdominal CT Datasets: A Critical Review of Bias, Clinical Relevance, and Real-world Applicability

Saeide Danaei, Zahra Dehghanian, Elahe Meftah, Nariman Naderi, Seyed Amir Ahmad Safavi-Naini, Faeze Khorasanizade, Hamid R. Rabiee

机构 * Data Science and Machine Learning Lab (DML), Department of Computer Engineering, Sharif University of Technology（数据科学与机器学习实验室（DML），计算机工程系，谢里夫大学） ； Data-Driven and Digital Health (D3M), The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai（数据驱动与数字健康（D3M），查尔斯·布朗弗曼个性化医学研究所，辛辛那提医学院） ； Shahid Beheshti University of Medical Sciences（沙希德·贝赫什提医学科学大学） ； Tehran University of Medical Sciences Cancer Research Institute（德黑兰医学院医学科学癌症研究所） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

Comments Preprint. Submitted to IEEE Journal of Biomedical and Health Informatics (under review). 10 pages, 3 figures, 5 tables

MedVisionLlama: Leveraging Pre-Trained Large Language Model Layers to Enhance Medical Image Segmentation

Gurucharan Marthi Krishna Kumar, Aman Chadha, Janine Mendola, Amir Shmuel

机构 * Montreal Neurological Institute, McGill University（蒙特利尔神经科学研究所，麦吉尔大学） 纠错

专题命中 医学影像 ：medical image(title,abstract)；分类 cs.CV、eess.IV；diagnosis(comments)

Comments Accepted to the CVAMD Workshop (Computer Vision for Automated Medical Diagnosis) at the 2025 IEEE/CVF International Conference on Computer Vision (ICCVW 2025)

DINOMotion: advanced robust tissue motion tracking with DINOv2 in 2D-Cine MRI-guided radiotherapy

Soorena Salari, Catherine Spino, Laurie-Anne Pharand, Fabienne Lathuiliere, Hassan Rivaz, Silvain Beriault, Yiming Xiao

机构 * Department of Computer Science and Software Engineering, Concordia University（计算机科学与软件工程系，康科迪亚大学） ； Department of Electrical and Computer Engineering, Concordia University（电气与计算机工程系，康科迪亚大学） ； Elekta Ltd.（Elekta公司） ； Diagnos Medical Systems（Diagnos医疗系统） 纠错

专题命中 医学影像 ：MRI(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

Comments Accepted to IEEE Transactions on Biomedical Engineering (TMBE), 14 pages

Lung-DDPM: Semantic Layout-guided Diffusion Models for Thoracic CT Image Synthesis

Yifan Jiang, Yannick Lemaréchal, Sophie Plante, Josée Bafaro, Jessica Abi-Rjeile, Philippe Joubert, Philippe Després, Venkata Manem

机构 * Centre de recherche du CHU de Québec-Université Laval（魁北克大学拉瓦尔医院研究中心） ； Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval（魁北克大学拉瓦尔心血管与呼吸病学研究所） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；biomedical(comments)

Comments Accepted by IEEE Transactions on Biomedical Engineering (TBME)

Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation

Xi Zhang, Zaiqiao Meng, Jake Lever, Edmond S. L. Ho

机构 * School of Computing Science, University of Glasgow（计算科学学院，格拉斯哥大学） 纠错

专题命中 医学影像 ：radiology(title,abstract)；分类 cs.CV、cs.LG；biomedical(journal_ref)

Comments Accepted by BioNLP@ACL 2024

Journal ref Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, ACL 2024, pp. 624-634

Noise-Inspired Diffusion Model for Generalizable Low-Dose CT Reconstruction

Qi Gao, Zhihao Chen, Dong Zeng, Junping Zhang, Jianhua Ma, Hongming Shan

机构 * Institute of Science and Technology for Brain-inspired Intelligence（脑启发智能科学与技术研究院） ； Fudan University（复旦大学） ； School of Biomedical Engineering（生物医学工程学院） ； Southern Medical University（南方医科大学） ； School of Computer Science（计算机科学学院） ； Xi’an Jiaotong University（西安交通大学） ； School of Life Science and Technology（生命科学与技术学院） ； MOE Frontiers Center for Brain Science（教育部脑科学前沿中心） ； Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Ministry of Education)（教育部计算神经科学与脑启发智能重点实验室） ； State Key Laboratory of Brain Function and Disorders（脑功能与疾病国家重点实验室） 纠错

专题命中 医学影像 ：CT(title,abstract)；分类 cs.CV、eess.IV；medical image(comments)

Comments Accepted for publication in Medical Image Analysis, 2025