arXivDaily arXiv每日学术速递 周一至周五更新

科学与医疗

医学 AI

医学智能、临床 AI、医学影像、病理、诊断和医疗健康大模型。

2026-02-13 至 2026-02-13 共收录 13 信号源:cs.CV, cs.LG, q-bio, eess.IV, eess.SP

1. 医学影像 13 篇

2403.17770 2026-02-13 eess.IV cs.CV 84%

CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation

基于条件扩散模型的CT合成用于腹部淋巴结分割

Yongrui Yu, Hanyu Chen, Zitian Zhang, Qiong Xiao, Wenhui Lei, Linrui Dai, Yu Fu, Hui Tan, Guan Wang, Peng Gao, Xiaofan Zhang

机构 * Shanghai Jiao Tong University, Shanghai, China(上海交通大学) Department of Surgical Oncology and General Surgery, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Hospital of China Medical University, Shenyang, China(外科肿瘤科和普通外科,精准诊断与治疗胃肠肿瘤国家重点实验室,教育部,中国医科大学第一附属医院,沈阳,中国) Department of Radiology, The First Hospital of China Medical University, Shenyang, China(放射科,中国医科大学第一附属医院,沈阳,中国) Shanghai AI Laboratory, Shanghai, China(上海人工智能实验室,上海,中国)

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

AI总结 本文提出LN-DDPM模型,通过条件扩散模型生成腹部淋巴结数据,提升分割性能。

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2505.02784 2026-02-13 cs.CV 83%

Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge

自动化胎儿脑MRI分割与生物测量的进展:来自FeTA 2024挑战的见解

Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp, Margaux Roulet, Diego Fajardo-Rojas, Liu Li, Jana Hutter, Hongwei Bran Li, Matthew Barkovich, Hui Ji, Luca Wilhelmi, Aline Dändliker, Céline Steger, Mériam Koob, Yvan Gomez, Anton Jakovčić, Melita Klaić, Ana Adžić, Pavel Marković, Gracia Grabarić, Milan Rados, Jordina Aviles Verdera, Gregor Kasprian, Gregor Dovjak, Raphael Gaubert-Rachmühl, Maurice Aschwanden, Qi Zeng, Davood Karimi, Denis Peruzzo, Tommaso Ciceri, Giorgio Longari, Rachika E. Hamadache, Amina Bouzid, Xavier Lladó, Simone Chiarella, Gerard Martí-Juan, Miguel Ángel González Ballester, Marco Castellaro, Marco Pinamonti, Valentina Visani, Robin Cremese, Keïn Sam, Fleur Gaudfernau, Param Ahir, Mehul Parikh, Maximilian Zenk, Michael Baumgartner, Klaus Maier-Hein, Li Tianhong, Yang Hong, Zhao Longfei, Domen Preloznik, Žiga Špiclin, Jae Won Choi, Muyang Li, Jia Fu, Guotai Wang, Jingwen Jiang, Lyuyang Tong, Bo Du, Andrea Gondova, Sungmin You, Kiho Im, Abdul Qayyum, Moona Mazher, Steven A Niederer, Andras Jakab, Roxane Licandro, Kelly Payette, Meritxell Bach Cuadra

机构 * organization= Department of Radiology, Lausanne University Hospital University of Lausanne , city= Lausanne , country= Switzerland organization= CIBM Center for Biomedical Imaging , city= Lausanne , country= Switzerland organization= Department of Early Life Imaging, School of Biomedical Engineering \& Imaging Sciences, King’s College London , city= London , country= UK organization= Smart Imaging Lab, University Hospital Erlangen , city= Erlangen , country= Germany organization= Center for MR-Research, University Children’s Hospital Zurich, University of Zurich , city= Zurich , country= Switzerland organization= Neuroscience Center Zurich, University of Zurich , city= Zurich , country= Switzerland organization= National Heart \& Lung Institute, Imperial College London , city= London , country= UK organization= University of California, San Francisco UCSF Benioff Children’s Hospital , city= San Francisco , state= California , country= USA organization= Department of Quantitative Biomedicine, University of Zurich , city= Zurich , country= Switzerland organization= Department of Informatics, Technical University of Munich , city= Munich , country= Germany organization= Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA organization= Neuroimaging Unit, Scientific Institute IRCCS E. Medea , city= Bosisio Parini , country= Italy organization= Department of Informatics, Systems Communication, University of Milano Bicocca , city= Milan , country= Italy organization= Research Institute of Computer Vision organization= BCN MedTech, Department of Engineering, Universitat Pompeu Fabra , city= Barcelona , country= Spain organization= Department of Information Engineering, University of Padova , city= Padova , country= Italy organization= Institut Pasteur, Université Paris Cité, CNRS UMR 3571, Decision organization= Inria, HeKA, PariSantéCampus , city= Paris , country= France organization= L. D. College of Engineering , city= Gujarat , country= India organization= Medical Faculty Heidelberg, Heidelberg University , addressline= Pattern Analysis Learning Group, Department of Radiation Oncology, Heidelberg University Hospital , city= Heidelberg , country= Germany organization= Canon Medical Systems (China) Co., Ltd , city= , country= China organization= Faculty of Electrical Engineering, University of Ljubljana , city= Ljubljana , country= Slovenia organization= Department of Radiology, Seoul National University Hospital , city= Seoul , country= South Korea organization= School of Mechanical Electrical Engineering, University of Electronic Science organization= School of Computer Science, Wuhan University , city= Wuhan , country= China Developmental Science Center, Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA organization= Hawkes Institute, Department of Computer Science, University College London , city= London , country= UK organization= Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School , city= Charlestown , state= Massachusetts , country= USA organization= Department of Biomedical Imaging Image-guided Therapy, Computational Imaging Research Lab (CIR), Early Life Image Analysis Group, Medical University of Vienna , city= Vienna , country= Austria organization= University Research Priority Project Adaptive Brain Circuits in Development Learning (AdaBD), University of Zurich , city= Zurich , country= Switzerland organization= Sagol Brain Institute, Tel Aviv Sourasky Medical Center School of EE, Tel-Aviv University , city= Tel-Aviv , country= Israel organization= Department of Medical Imaging Sciences, The Faculty of Social Welfare Health Sciences, University of Haifa , city= Haifa , country= Israel Faculty of Medicine Sagol School of Neuroscience, Tel-Aviv University , city= Tel-Aviv , country= Israel organization= Department Woman-Mother-Child, CHUV , city= Lausanne , country= Switzerland organization= BCNatal Fetal Medicine Research Center (Hospital Clínic Hospital Sant Joan de Déu), Universitat de Barcelona , city= Barcelona , country= Spain organization= German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing , city= Heidelberg , country= Germany organization= Helmholtz Imaging, German Cancer Research Center (DKFZ) , city= Heidelberg , country= Germany organization= Faculty of Mathematics Computer Science, Heidelberg University , city= Heidelberg , country= Germany organization= University of Zurich , city= Zurich , country= Switzerland organization= Croatian Institute for Brain Research, School of Medicine, University of Zagreb , city= Zagreb , country= Croatia organization= Department of Biomedical Engineering, School of Biomedical Engineering \& Imaging Sciences, King’s College , city= London , country= United Kingdom Musculoskeletal Radiology, Medical University of Vienna , city= Vienna , country= Austria organization= Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA organization= Department of Radiology, Boston Children’s Hospital, Harvard Medical School , city= Boston , state= Massachusetts , country= USA

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

AI总结 FeTA 2024挑战通过引入生物测量预测和低场MRI数据,推动了胎儿脑MRI分割与生物测量的自动化进展,揭示了拓扑差异和成像系统对分割性能的影响。

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2512.13101 2026-02-13 cs.CV cs.AI cs.LG 81%

Harmonizing Generalization and Specialization: Uncertainty-Informed Collaborative Learning for Semi-supervised Medical Image Segmentation

协调泛化与专门化:基于不确定性的协作学习用于半监督医学图像分割

Wenjing Lu, Yi Hong, Yang Yang

机构 * AGI Institute, School of Computer Science, Shanghai Jiao Tong University(AGI研究院,计算机科学学院,上海交通大学)

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

AI总结 本文提出UnCoL框架,通过双教师机制协调半监督医学图像分割中的泛化与专门化,利用不确定性指导伪标签学习以提升分割性能。

Comments Accepted for publication in IEEE Transactions on Medical Imaging (TMI), 2026

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2503.10156 2026-02-13 eess.IV cs.CV 81%

Automatic quality control in multi-centric fetal brain MRI super-resolution reconstruction

多中心胎儿脑部MRI超分辨率重建中的自动质量控制

Thomas Sanchez, Vladyslav Zalevskyi, Angeline Mihailov, Gerard Martí-Juan, Elisenda Eixarch, Andras Jakab, Vincent Dunet, Mériam Koob, Guillaume Auzias, Meritxell Bach Cuadra

机构 * CIBM -- Center for Biomedical Imaging(CIBM生物医学成像中心) Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne(诊断与介入放射学系,洛桑大学医院和洛桑大学) Aix-Marseille Université(阿维尼昂-马赛大学) BCN MedTech(BCN医疗技术) BCNatal Fetal Medicine Research Center(BCNatal胎儿医学研究中心) IDIBAPS and CIBERER(IDIBAPS与CIBERER) Center for MR Research(磁共振研究中心) Neuroscience Center Zurich(苏黎世神经科学中心) Research Priority Project Adaptive Brain Circuits in Development and Learning (AdaBD)(发展与学习适应性脑回路研究优先项目)

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

AI总结 本文提出FetMRQC_SR方法,通过机器学习提取100+图像质量指标,实现胎儿脑MRI超分辨率重建的质量自动控制,验证其在域外数据下的高性能。

Comments 14 pages, 5 figures; accepted at the 2025 MICCAI Perinatal, Preterm and Paediatric Image Analysis (PIPPI) Workshop

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2306.03284 2026-02-13 cs.LG eess.IV 81%

Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models

利用扩散生成模型优化压缩感知MRI的采样模式

Sriram Ravula, Brett Levac, Yamin Arefeen, Ajil Jalal, Alexandros G. Dimakis, Jonathan I. Tamir

机构 * Chandra Family Department of Electrical and Computer Engineering, The University of Texas at Austin(查德拉家族电子与计算机工程系,德克萨斯大学奥斯汀分校) The University of Texas at Austin(德克萨斯大学奥斯汀分校) Imaging Physics, MD Anderson Cancer Center, Houston, Texas, USA(影像物理,MD安德森癌症中心,休斯顿,德克萨斯州,美国) Electrical Engineering and Computer Sciences, University of California, Berkeley(电气工程与计算机科学,加州大学伯克利分校) Department of Diagnostic Medicine, Dell Medical School, Austin, Texas, USA(诊断医学系,德勒医学学院,奥斯汀,德克萨斯州,美国)

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

AI总结 本文提出利用扩散模型优化MRI采样模式,以提高加速多通道MRI重建的质量。

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2602.11880 2026-02-13 cs.CV cs.AI 79%

SynthRAR: Ring Artifacts Reduction in CT with Unrolled Network and Synthetic Data Training

SynthRAR: 通过展开网络和合成数据训练的CT环状伪影减少

Hongxu Yang, Levente Lippenszky, Edina Timko, Gopal Avinash

机构 * Science&Technology Organization, GE HealthCare(科学与技术组织,通用电气医疗)

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

AI总结 SynthRAR通过展开网络和合成数据训练,有效减少CT环状伪影,无需真实临床数据即可提升重建图像质量。

Comments Prepare for submission

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2510.17436 2026-02-13 eess.IV 79%

Segmenting infant brains across magnetic fields: Domain randomization and annotation curation in ultra-low field MRI

在磁场中分割婴儿大脑:在超低场MRI中域随机化和标注整理

Vladyslav Zalevskyi, Dondu-Busra Bulut, Thomas Sanchez, Meritxell Bach Cuadra

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

AI总结 本文提出域随机化框架,通过提升标注质量与数据增强,实现超低场MRI中婴儿大脑分割的准确性和鲁棒性。

Comments 1st place (hippocampus) and 3rd place (basal ganglia) in the Low field pediatric brain magnetic resonance Image Segmentation and quality Assurance Challenge (LISA) 2025

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2503.17600 2026-02-13 physics.med-ph eess.SP 79%

Imaging Intravoxel Vessel Size Distribution in the Brain Using Susceptibility Contrast Enhanced MRI

利用磁共振成像的磁 susceptibility 对比度分析脑内 voxel 内血管尺寸分布

Natenael B. Semmineh, Indranil Guha, Deborah Healey, Anagha Chandrasekharan, Jerrold L. Boxerman, C. Chad Quarles

专题命中 医学影像 :MRI(title,abstract);分类 eess.SP

AI总结 本文提出一种基于磁 susceptibility 对比度的 MRI 方法,用于分析脑内 voxel 内血管尺寸分布,以更全面评估血管重塑。

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2602.11625 2026-02-13 cs.CV cs.AI 79%

PLOT-CT: Pre-log Voronoi Decomposition Assisted Generation for Low-dose CT Reconstruction

PLOT-CT:预对数 Voronoi 分解辅助低剂量 CT 重建

Bin Huang, Xun Yu, Yikun Zhang, Yi Zhang, Yang Chen, Qiegen Liu

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

AI总结 PLOT-CT 通过预对数 Voronoi 分解提升低剂量 CT 重建精度,实现 2.36dB 的 PSNR 改进。

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2602.11436 2026-02-13 cs.CV cs.AI 74%

Fighting MRI Anisotropy: Learning Multiple Cardiac Shapes From a Single Implicit Neural Representation

对抗MRI各向异性:从单一隐式神经表示学习多种心脏形状

Carolina Brás, Soufiane Ben Haddou, Thijs P. Kuipers, Laura Alvarez-Florez, R. Nils Planken, Fleur V. Y. Tjong, Connie Bezzina, Ivana Išgum

机构 * Amsterdam UMC(阿姆斯特丹大学医学中心) University of Amsterdam(阿姆斯特丹大学) Informatics Institute(信息学院) QurAI group(QurAI组) Amsterdam Cardiovascular Sciences(阿姆斯特丹心血管科学) Department of Biomedical Engineering and Physics(生物医学工程与物理系) Department of Radiology and Nuclear Medicine(放射学与核医学系) Department of Radiology(放射学系) Mayo Clinic(梅奥诊所) Department of Clinical and Experimental Cardiology(临床与实验心脏病学系) Department of Experimental Cardiology(实验心脏病学系) Heart Failure & Arrhythmias(心力衰竭与心律失常)

专题命中 医学影像 :MRI(title);分类 cs.CV

AI总结 本文提出利用高分辨率CTA数据训练隐式神经网络,以解决MRI各向异性问题,实现更精确的心脏形状重建。

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2602.11628 2026-02-13 cs.CV cs.LG 73%

PLESS: Pseudo-Label Enhancement with Spreading Scribbles for Weakly Supervised Segmentation

PLESS: 基于扩散涂鸦的伪标签增强用于弱监督分割

Yeva Gabrielyan, Varduhi Yeghiazaryan, Irina Voiculescu

机构 * Akian College of Science and Engineering, American University of Armenia(阿塞拜疆美国大学科学与工程学院) Department of Computer Science, University of Oxford(牛津大学计算机科学系)

专题命中 医学影像 :medical image(abstract);MRI(abstract);分类 cs.CV、cs.LG

AI总结 PLESS通过扩散涂鸦信息提升伪标签可靠性,改进弱监督分割性能。

Comments This work was supported by the Afeyan Family Foundation Seed Grants and the JACE Foundation Research Innovation Grant Program at AUA

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2602.11942 2026-02-13 cs.CV cs.AI 57%

Synthesis of Late Gadolinium Enhancement Images via Implicit Neural Representations for Cardiac Scar Segmentation

通过隐式神经表示合成晚期钆增强图像用于心脏瘢痕分割

Soufiane Ben Haddou, Laura Alvarez-Florez, Erik J. Bekkers, Fleur V. Y. Tjong, Ahmad S. Amin, Connie R. Bezzina, Ivana Išgum

机构 * Amsterdam UMC, The Netherlands(阿姆斯特丹大学医学中心,荷兰) University of Amsterdam, The Netherlands(阿姆斯特丹大学,荷兰) Informatics Institute, University of Amsterdam, The Netherlands(阿姆斯特丹大学信息学院,荷兰) Amsterdam Cardiovascular Sciences, Amsterdam UMC, The Netherlands(阿姆斯特丹心血管科学,阿姆斯特丹大学医学中心,荷兰) Amsterdam Machine Learning Lab, University of Amsterdam, The Netherlands(阿姆斯特丹机器学习实验室,阿姆斯特丹大学,荷兰) Department of Biomedical Engineering and Physics, Amsterdam UMC, The Netherlands(生物医学工程与物理系,阿姆斯特丹大学医学中心,荷兰) Department of Experimental Cardiology, Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam UMC, The Netherlands(实验心脏病学系,阿姆斯特丹心血管科学,心力衰竭与心律失常,阿姆斯特丹大学医学中心,荷兰) Department of Cardiology, Amsterdam UMC, The Netherlands(心脏病学系,阿姆斯特丹大学医学中心,荷兰) Department of Radiology and Nuclear Medicine, Amsterdam UMC, The Netherlands(放射学与核医学系,阿姆斯特丹大学医学中心,荷兰) Department of Radiology, Mayo Clinic, Rochester, United States of America(放射学系,梅奥诊所,罗切斯特,美国)

专题命中 医学影像 :MRI(abstract);分类 cs.CV

AI总结 本文提出利用隐式神经表示和扩散模型合成LGE图像,以提高心脏瘢痕分割的性能,通过生成合成数据缓解标注数据不足的问题。

Comments Paper accepted at SPIE Medical Imaging 2026 Conference

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2602.11705 2026-02-13 cs.CV 57%

TG-Field: Geometry-Aware Radiative Gaussian Fields for Tomographic Reconstruction

TG-Field:基于几何的辐射高斯场用于断层扫描重建

Yuxiang Zhong, Jun Wei, Chaoqi Chen, Senyou An, Hui Huang

专题命中 医学影像 :CT(abstract);分类 cs.CV

AI总结 TG-Field通过几何感知高斯变形框架,提升静态和动态CT重建的精度与效率,尤其在稀疏投影条件下表现优异。

Comments Accepted to AAAI 2026. Project page: https://vcc.tech/research/2026/TG-Field

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