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。

共收录 22709 信号源:cs.CV, cs.LG, q-bio, eess.IV, eess.SP

1. 医学影像 22709 篇

2605.16408 2026-05-19 cs.CV 84%

Visual Search Patterns in 3D Pancreatic Imaging: An Eye Tracking Study

三维胰腺成像中的视觉搜索模式:一项眼动研究

Anna Anikina, Leila Khaertdinova, Trine Balschmidt, Michael B Andersen, Christoph F Müller, Erik GS Brandt, Henrik S Thomsen, Claudia Mello-Thoms, Bulat Ibragimov

机构 * Department of Computer Science, University of Copenhagen(哥本哈根大学计算机科学系) Department of Radiology, Herlev Hospital(赫尔勒夫医院放射科) Department of Radiology, University of Iowa(爱荷华大学放射科)

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

AI总结 本研究通过眼动追踪分析三维胰腺CT影像中放射科医生的视觉搜索行为,揭示其在空间和时间上的注视模式,为理解诊断策略提供新的视角。

Comments Accepted at SPIE - Medical Imaging Conference 2026

Journal ref Proc. SPIE 13928, Medical Imaging 2026: Image Perception, Observer Performance, and Technology Assessment, 1392814 (2026)

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2605.16393 2026-05-19 cs.CV cs.AI 84%

Vision Transformer-Conditioned UNet for Domain-Adaptive Semantic Segmentation

基于 Vision Transformer 的 UNet 用于领域自适应语义分割

Joel Valdivia Ortega, Tingying Peng, Marion Jasnin

机构 * Helmholtz Pioneer Campus, Helmholtz Munich, Neuherberg, Germany(海德堡先锋校园,海德堡穆恩奇,纽赫尔伯格,德国) School of Computation, Information and Technology, TUM, Garching, Germany(计算、信息与技术学院,技术大学慕尼黑,冈辛,德国) Department of Chemistry, TUM, Garching, Germany(化学系,技术大学慕尼黑,冈辛,德国)

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

AI总结 本文提出 ViTC-UNet,通过可学习令牌和双向注意力解码器将预训练 ViT 表示条件化于 UNet,以提升生物医学语义分割的精度与适应性。

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2605.13686 2026-05-14 cs.CV cs.AI 84%

Cross Modality Image Translation In Medical Imaging Using Generative Frameworks

利用生成框架在医学影像中实现跨模态图像翻译

Giulia Romoli, Alessia Capoccia, Filippo Ruffini, Francesco Di Feola, Luca Boldrini, Arturo Chiti, Renato Cuocolo, Tugba Akinci D'Antonoli, Fatemeh Darvizeh, Marcello Di Pumpo, Bradley J. Erickson, Liu Fang, Deborah Fazzini, Paola Feraco, Fabrizia Gelardi, Francesco Gossetti, Ana Isabel Hernáiz Ferrer, Michail E. Klontzas, Seyedmehdi Payabvash, Katrine Riklund, Sara N. Strandberg, Valerio Guarrasi, Paolo Soda

机构 * Department of Diagnostics and Intervention, Radiation Physics, Biomedical Engineering, Umeå University(诊断与介入部门、放射物理、生物医学工程,乌梅大学) Unit of Artificial Intelligence and Computer Systems, Department of Engineering, Università Campus Bio-Medico di Roma(人工智能与计算机系统单位,工程部门,罗马生物医学学院) Vita-Salute San Raffaele University(维塔-萨拉特·桑拉法埃莱大学) Department of Medicine, Surgery and Dentistry, University of Salerno(医学、外科和牙科部门,萨勒诺大学) Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel(诊断和介入神经放射学部门,放射学部门,巴塞尔大学医院) Department of Pediatric Radiology, University Children’s Hospital Basel(儿科放射学部门,巴塞尔儿童医院) Department of Life Science and Public Health, Università Cattolica del Sacro Cuore(生命科学与公共健康部门,圣心大学) Athinoula A. Martinos Center for Biomedical Imaging(阿提诺拉A·马里诺斯生物医学成像中心) Artificial Intelligence and Translational Imaging (ATI) Lab, Department of Radiology, School of Medicine, University of Crete(人工智能与转化成像(ATI)实验室,放射学部门,医学院,克里特大学) Division of Radiology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute(放射学部门,临床科学、介入和科技(CLINTEC)部门,卡罗林斯卡研究所) Columbia University Medical Center(哥伦比亚大学医学中心) Department of Diagnostics and intervention, Diagnostic radiology, Umeå University(诊断与介入部门,诊断放射学,乌梅大学)

专题命中 医学影像 :MRI(abstract,abstract_cn);CT(abstract,abstract_cn);medical image(abstract);分类 cs.CV

AI总结 本文提出了一种标准化的3D医学图像跨模态翻译评估框架,比较了七种生成模型在不同数据集上的性能,揭示了GANs在不同任务中优于潜在生成模型,并发现合成影像在临床应用中难以区分。

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2605.10002 2026-05-12 cs.CV 84%

Med-StepBench: A Hierarchical Reasoning Framework for Evaluating Hallucinations in Medical Vision-Language Models

Med-StepBench:一种用于评估医学视觉-语言模型幻觉的分层推理框架

Minh Khoi Nguyen, Dai Lam Le, Amir Reza Jafari, Tuan Dung Nguyen, Mai Hong Son, Mai Huy Thong, Quang Huy Nguyen, Thanh Trung Nguyen, Reza Farahbakhsh, Noel Crespi, Phi Le Nguyen

机构 * AI4LIFE, Hanoi University of Science and Technology, Vietnam(AI4LIFE,越南科学与技术大学) SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris, France(SAMOVAR,法国电信南巴黎学院,巴黎理工学院) Military Central Hospital, Vietnam(越南108军中心医院)

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

AI总结 本文提出Med-StepBench,首个针对3D肿瘤PET/CT图像的分步幻觉检测基准,通过12000张图像和100万对图像-陈述数据,揭示了现有VLMs在多步临床推理中的系统性缺陷。

Comments Accepted at IJCAI-ECAI 2026

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2508.06805 2026-05-11 cs.CV 84%

Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsampling

通过自上而下细化和子像素上采样进行器官边界检测

Aarav Mehta, Priya Deshmukh, Vikram Singh, Siddharth Malhotra, Krishnan Menon Iyer, Tanvi Iyer

专题命中 医学影像 :MRI(abstract,abstract_cn);CT(abstract,abstract_cn);medical image(abstract);分类 cs.CV

AI总结 本文提出一种医学聚焦的清晰边缘检测器,通过自上而下反向细化架构和子像素上采样,提升器官边界定位精度,实验表明在严格标准下优于传统方法,提升分割、配准和病变界定效果。

Comments arXiv admin note: This submission has been withdrawn due to violation of arXiv policies for acceptable submissions

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2603.02727 2026-05-04 cs.CV 84%

Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation

门控差分线性注意力:一种线性时间的解码器用于高保真的医学分割

Hongbo Zheng, Afshin Bozorgpour, Dorit Merhof, Minjia Zhang

机构 * University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校) University of Regensburg(莱茵-瓦尔登堡大学)

专题命中 医学影像 :MRI(abstract,abstract_cn);CT(abstract,abstract_cn);medical image(abstract);分类 cs.CV

AI总结 本文提出一种线性时间解码器,通过门控差分线性注意力在保持细密解剖边界的同时提升医学图像分割的效率和精度。

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2412.10441 2026-04-29 cs.GR cs.AI cs.CV 84%

Novel 3D Binary Indexed Tree for Volume Computation of 3D Reconstructed Models from Volumetric Data

新颖的3D二进制索引树用于从体数据中计算3D重建模型的体积

Quoc-Bao Nguyen-Le, Tuan-Hy Le, Anh-Triet Do

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

AI总结 本文提出了一种结合多元微积分、 marching cube算法和二进制索引树数据结构的算法,用于高效计算从CT或MR获取的体数据的内在体积,通过30种体积值配置实现快速查询和模型编辑。

Comments This paper has been withdrawn by the author. After further review, the author believes that the current version does not meet the desired standards and plans to revise the work before any potential resubmission

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2604.11176 2026-04-17 cs.CV 84%

Precision Synthesis of Multi-Tracer PET via VLM-Modulated Rectified Flow for Stratifying Mild Cognitive Impairment

多示踪PET的高精度合成通过VLM调制的校正流用于区分轻度认知障碍

Tuo Liu, Shuijin Lin, Shaozhen Yan, Haifeng Wang, Jie Lu, Jianhua Ma, Chunfeng Lian

机构 * School of Mathematics and Statistics, Xi'an Jiaotong University(西安交通大学数学与统计学学院) Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University(教育部生物医学信息工程重点实验室,西安交通大学生命科学与技术学院) Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University(首都医科大学宣武医院放射科与核医学科) Research Center for Intelligent Medical Equipment and Devices (IMED), Xi'an Jiaotong University(智能医疗设备与器件研究中心(IMED),西安交通大学)

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

AI总结 本文提出DIReCT$++$模型,结合MRI和临床信息,通过校正流和视觉语言模型生成高保真多示踪PET图像,实现轻度认知障碍的精准分层。

Comments Added supplementary material

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2604.11835 2026-04-15 cs.LG cs.AI 84%

Schema-Adaptive Tabular Representation Learning with LLMs for Generalizable Multimodal Clinical Reasoning

基于LLM的Schema自适应表格表示学习用于通用多模态临床推理

Hongxi Mao, Wei Zhou, Mengting Jia, Tao Fang, Huan Gao, Bin Zhang, Shangyang Li

机构 * Beijing University of Posts and Telecommunications(北京邮电大学) Boston University(波士顿大学) University of Southern California(南加州大学) GDIIST Renyixun Health Technology Co., Ltd.(仁心迅健康科技有限公司)

专题命中 医学影像 :MRI(summary_cn,abstract);diagnosis(abstract);分类 cs.LG

AI总结 本文提出基于LLM的Schema自适应表格表示学习方法,通过将结构化变量转换为语义自然语言并编码,实现零样本跨schema对齐,结合表格和MRI数据在多模态 dementia 诊断中取得优于临床基准的性能。

Comments 11 pages, 4 figures

Journal ref ACL 2026, Main conference

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2603.18545 2026-04-06 cs.CV cs.AI 84%

CoDA: Exploring Chain-of-Distribution Attacks and Post-Hoc Token-Space Repair for Medical Vision-Language Models

CoDA:探索链式分布攻击及事后令牌空间修复用于医疗视觉-语言模型

Xiang Chen, Fangfang Yang, Chunlei Meng, Yuxian Dong, Ang Li, Yiwei Wei, Jiahuan Long, Jiujiang Guo, Chengyin Hu

专题命中 医学影像 :medical image(abstract);MRI(abstract);CT(abstract);pathology(abstract)

AI总结 本文提出CoDA框架,通过构建临床合理的流程偏移,评估医疗视觉-语言模型在真实临床工作流中的可靠性,发现零样本性能显著下降,并引入事后修复策略提升准确性。

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2505.19208 2026-03-19 cs.CV 84%

Domain and Task-Focused Example Selection for Data-Efficient Contrastive Medical Image Segmentation

面向领域和任务的示例选择用于数据高效的对比医学图像分割

Tyler Ward, Aaron Moseley, Abdullah-Al-Zubaer Imran

机构 * Department of Computer Science, University of Kentucky(肯塔基大学计算机科学系)

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

AI总结 本文提出PolyCL框架,通过对比学习提升医学图像分割效率,无需像素级标注,结合SAM模型提升分割精度与体积分割能力。

Comments Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://www.melba-journal.org/2026:002

Journal ref Machine.Learning.for.Biomedical.Imaging. 2026 (2026)

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2510.17999 2026-02-23 cs.CV 84%

Investigating Demographic Bias in Brain MRI Segmentation: A Comparative Study of Deep-Learning and Non-Deep-Learning Methods

研究脑部MRI分割中的人口统计学偏差:深度学习与非深度学习方法的比较研究

Ghazal Danaee, Marc Niethammer, Jarrett Rushmore, Sylvain Bouix

机构 * École de technologie supérieure University of California San Diego(加州大学圣地亚哥分校) Boston University School of Medicine(波士顿大学医学院)

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

AI总结 本研究比较了深度学习和非深度学习方法在脑MRI分割中的性能,发现种族匹配数据能提升分割准确性,但种族效应在部分模型中消失。

Comments 17 pages, 2 figures, Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2025:035

Journal ref Machine.Learning.for.Biomedical.Imaging. " (2026)

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2406.17608 2026-01-05 cs.CV 84%

Test-time generative augmentation for medical image segmentation

测试时生成增强用于医学图像分割

Xiao Ma, Yuhui Tao, Zetian Zhang, Yuhan Zhang, Xi Wang, Sheng Zhang, Zexuan Ji, Yizhe Zhang, Qiang Chen, Guang Yang

机构 * organization= School of Computer Science Engineering, Nanjing University of Science organization= Bioengineering Department Imperial-X, Imperial College London , city= London , postcode= W12 7SL , country= UK organization= Digital Medical Research Center, School of Basic Medical Sciences, Fudan University , city= Shanghai , country= China organization= Shanghai Key Laboratory of MICCAI , city= Shanghai , country= China organization= School of Biomedical Engineering, Shenzhen University , city= Shenzhen , country= China organization= Department of Computer Science Engineering, The Hong Kong University of Science Engineering, The Chinese University of Hong Kong , city= Hong Kong , country= China Lung Institute, Imperial College London , city= London , postcode= SW7 2AZ , country= UK organization= Cardiovascular Research Centre, Royal Brompton Hospital , city= London , postcode= SW3 6NP , country= UK organization= School of Biomedical Engineering \& Imaging Sciences, King's College London , city= London , postcode= WC2R 2LS , country= UK

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

AI总结 本研究提出TTGA方法,通过生成模型在测试时增强医学图像分割,提升分割精度并提供像素级误差估计。

Comments Accepted for publication in Medical Image Analysis (MedIA). Finalized version. Vol. 109, March 2026

Journal ref Medical Image Analysis, Vol. 109, 103902, 2026

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2508.10947 2025-08-18 cs.CV 84%

MedAtlas: Evaluating LLMs for Multi-Round, Multi-Task Medical Reasoning Across Diverse Imaging Modalities and Clinical Text

Ronghao Xu, Zhen Huang, Yangbo Wei, Xiaoqian Zhou, Zikang Xu, Ting Liu, Zihang Jiang, S. Kevin Zhou

专题命中 医学影像 :medical AI(abstract);medical image(abstract);MRI(abstract);CT(abstract)

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2506.14136 2025-06-18 cs.CV 84%

Interpreting Biomedical VLMs on High-Imbalance Out-of-Distributions: An Insight into BiomedCLIP on Radiology

Nafiz Sadman, Farhana Zulkernine, Benjamin Kwan

机构 * School of Computing(计算学院) Department of Diagnostic Radiology(诊断放射科) Queen's University(皇后大学) Kingston Health Sciences Centre(金斯顿健康科学中心)

专题命中 医学影像 :radiology(title);biomedical(title);分类 cs.CV

Comments GitHub: https://github.com/Nafiz95/BioVLM_Eval_CXR

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2408.08070 2025-05-15 cs.CV 84%

MambaMIM: Pre-training Mamba with State Space Token Interpolation and its Application to Medical Image Segmentation

Fenghe Tang, Bingkun Nian, Yingtai Li, Zihang Jiang, Jie Yang, Wei Liu, S. Kevin Zhou

机构 * School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China(科学技术大学生物医学工程学院) Suzhou Institute for Advanced Research, University of Science and Technology of China(科学技术大学苏州市先进研究所) Center for Medical Imaging, Robotics, and Analytic Computing & LEarning (MIRACLE), Suzhou Institute for Advanced Research, USTC(医学影像、机器人与分析计算与学习中心) Department of Automation, Shanghai Jiao Tong University(上海交通大学自动化系) Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University(上海交通大学图像处理与模式识别研究所) Institute of Medical Robotics, Shanghai Jiao Tong University(上海交通大学医学机器人研究所) State Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China(科学技术大学精密与智能化学国家重点实验室)

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

Comments Accepted by Medical Image Analysis. Code: https://github.com/FengheTan9/MambaMIM

Journal ref Medical Image Analysis, Volume 103, 2025, Article 103606

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2504.07336 2025-04-11 cs.CV cs.AI 84%

Zeus: Zero-shot LLM Instruction for Union Segmentation in Multimodal Medical Imaging

Siyuan Dai, Kai Ye, Guodong Liu, Haoteng Tang, Liang Zhan

专题命中 医学影像 :medical image(abstract);MRI(abstract);CT(abstract);diagnosis(abstract)

Comments 21 pages, 4 figures, In Press by a journal

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2503.21836 2025-03-31 cs.CV 84%

iMedImage Technical Report

Ran Wei, ZhiXiong Lan, Qing Yan, Ning Song, Ming Lv, LongQing Ye

专题命中 医学影像 :medical image(abstract);MRI(abstract);CT(abstract);pathology(abstract)

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2410.03406 2024-10-10 stat.ML cs.LG 84%

Conformal confidence sets for biomedical image segmentation

Samuel Davenport

专题命中 医学影像 :medical image(title);biomedical(title);分类 cs.LG

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2407.17380 2024-09-27 eess.IV cs.CV q-bio.QM 84%

2D and 3D Deep Learning Models for MRI-based Parkinson's Disease Classification: A Comparative Analysis of Convolutional Kolmogorov-Arnold Networks, Convolutional Neural Networks, and Graph Convolutional Networks

Salil B Patel, Vicky Goh, James F FitzGerald, Chrystalina A Antoniades

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

Comments 7 figures

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2211.01885 2022-11-04 eess.IV cs.CV q-bio.QM 84%

Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Images

Jason Walsh, Alice Othmani, Mayank Jain, Soumyabrata Dev

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

Comments Published in Healthcare Analytics, 2022

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2207.14781 2022-08-01 cs.CV cs.LG q-bio.QM 84%

Using Multi-modal Data for Improving Generalizability and Explainability of Disease Classification in Radiology

Pranav Agnihotri, Sara Ketabi, Khashayar, Namdar, Farzad Khalvati

专题命中 医学影像 :radiology(title,abstract);diagnosis(abstract);分类 cs.CV、cs.LG、q-bio

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2206.12980 2022-07-08 eess.IV cs.CV q-bio.QM 84%

Detecting Schizophrenia with 3D Structural Brain MRI Using Deep Learning

Junhao Zhang, Vishwanatha M. Rao, Ye Tian, Yanting Yang, Nicolas Acosta, Zihan Wan, Pin-Yu Lee, Chloe Zhang, Lawrence S. Kegeles, Scott A. Small, Jia Guo

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

Comments 13 pages, 6 figures

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2206.05052 2022-06-13 cs.LG cs.AI eess.IV q-bio.NC 84%

Meta-data Study in Autism Spectrum Disorder Classification Based on Structural MRI

Ruimin Ma, Yanlin Wang, Yanjie Wei, Yi Pan

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

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2203.00628 2022-03-25 q-bio.QM cs.LG eess.IV 84%

A Neural Ordinary Differential Equation Model for Visualizing Deep Neural Network Behaviors in Multi-Parametric MRI based Glioma Segmentation

Zhenyu Yang, Zongsheng Hu, Hangjie Ji, Kyle Lafata, Scott Floyd, Fang-Fang Yin, Chunhao Wang

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

Comments 30 pages, 7 figures, 2 tables

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2110.14775 2021-11-02 cs.CV cs.AI 84%

BI-GCN: Boundary-Aware Input-Dependent Graph Convolution Network for Biomedical Image Segmentation

Yanda Meng, Hongrun Zhang, Dongxu Gao, Yitian Zhao, Xiaoyun Yang, Xuesheng Qian, Xiaowei Huang, Yalin Zheng

专题命中 医学影像 :medical image(title);biomedical(title);分类 cs.CV

Comments Accepted in BMVC2021 as Oral

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2104.04672 2021-05-31 q-bio.QM cs.CV cs.LG 84%

Deep Learning Identifies Neuroimaging Signatures of Alzheimer's Disease Using Structural and Synthesized Functional MRI Data

Nanyan Zhu, Chen Liu, Xinyang Feng, Dipika Sikka, Sabrina Gjerswold-Selleck, Scott A. Small, Jia Guo

专题命中 医学影像 :MRI(title,abstract);diagnosis(abstract);分类 cs.CV、cs.LG、q-bio

Comments Published in IEEE ISBI 2021. Available at https://ieeexplore.ieee.org/document/9433808

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1903.12331 2021-01-27 cs.CV eess.IV q-bio.QM 84%

A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural Network

Weiwei Zong, Joon Lee, Chang Liu, Eric Carver, Aharon Feldman, Branislava Janic, Mohamed Elshaikh, Milan Pantelic, David Hearshen, Indrin Chetty, Benjamin Movsas, Ning Wen

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

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2003.04655 2020-12-01 cs.CV eess.IV q-bio.QM 84%

Lung Infection Quantification of COVID-19 in CT Images with Deep Learning

Fei Shan, Yaozong Gao, Jun Wang, Weiya Shi, Nannan Shi, Miaofei Han, Zhong Xue, Dinggang Shen, Yuxin Shi

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

Comments 23 pages, 6 figures

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2006.15255 2020-06-30 q-bio.QM cs.LG eess.IV stat.ML 84%

Smile-GANs: Semi-supervised clustering via GANs for dissecting brain disease heterogeneity from medical images

Zhijian Yang, Junhao Wen, Christos Davatzikos

专题命中 医学影像 :medical image(title);MRI(abstract);biomedical(abstract);分类 cs.LG、q-bio、eess.IV

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