医学 AI - arXivDaily 专题

2005.13338 2020-05-28 cs.CV eess.IV 86%

Tackling the Problem of Large Deformations in Deep Learning Based Medical Image Registration Using Displacement Embeddings

Lasse Hansen, Mattias P. Heinrich

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

2002.03366 2020-02-20 eess.IV cs.CV 86%

MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data

Quande Liu, Qi Dou, Lequan Yu, Pheng Ann Heng

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

Comments IEEE TMI, 2020

2002.02255 2020-02-07 eess.IV cs.CV 86%

Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation

Cheng Chen, Qi Dou, Hao Chen, Jing Qin, Pheng Ann Heng

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

Comments IEEE TMI

1910.09198 2020-02-05 eess.IV cs.CV 86%

Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net

He Tang, Xiaobing Pei, Shilong Huang, Xin Li, Chao Liu

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

1908.07765 2019-08-22 eess.IV cs.CV 86%

Dataset Growth in Medical Image Analysis Research

Yuval Landau, Nahum Kiryati

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

1908.04346 2019-08-14 cs.CV eess.IV 86%

SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis

Tianyang Zhang, Huazhu Fu, Yitian Zhao, Jun Cheng, Mengjie Guo, Zaiwang Gu, Bing Yang, Yuting Xiao, Shenghua Gao, Jiang Liu

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

Comments Accepted to MICCAI 2019

1907.05598 2019-07-15 eess.IV cs.CV 86%

Coupled-Projection Residual Network for MRI Super-Resolution

Chun-Mei Feng, Kai Wang, Shijian Lu, Yong Xu, Heng Kong, Ling Shao

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

Comments Our source code will be publicly available at http://www.yongxu.org/lunwen.html

1907.03297 2019-07-09 eess.IV cs.CV 86%

Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis

Dong Nie, Lei Xiang, Qian Wang, Dinggang Shen

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

1903.04711 2019-03-13 cs.CV cs.LG cs.NE 86%

Deep Learning for Automated Medical Image Analysis

Wentao Zhu

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

Comments PhD Thesis

1803.01229 2019-01-23 cs.CV cs.LG stat.ML 86%

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

Maayan Frid-Adar, Idit Diamant, Eyal Klang, Michal Amitai, Jacob Goldberger, Hayit Greenspan

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

Comments Preprint submitted to Neurocomputing

2606.15976 2026-06-16 cs.CV 新提交 86%

HadBalance: A Plug-and-Play Unified Global Geometric Prior Framework for Generalizable Biomedical Segmentation

HadBalance: 一种即插即用的统一全局几何先验框架，用于可泛化的生物医学分割

Zhuangzhi Gao, Feixiang Zhou, He Zhao, Wenhan Chen, Ruiyu Luo, Xin Wang, Hongyi Qin, Zhongli Wu, Yanda Meng, Yitian Zhao, Alena Shantsila, Gregory Y. H. Lip, Eduard Shantsila, Yalin Zheng

机构 * Department of Eye and Vision Science, University of Liverpool（利物浦大学眼与视觉科学系）； Department of Primary Care and Mental Health, University of Liverpool（利物浦大学初级保健与精神健康系）； School of Psychological and Cognitive Sciences, Peking University（北京大学心理与认知科学学院）； Computer Vision Research Group, University of Amsterdam（阿姆斯特丹大学计算机视觉研究组）； Institute of Life Course & Medical Sciences, University of Liverpool（利物浦大学生命历程与医学科学研究所）； Bioengineering Program, Biomedical Sciences Division (BioMed), King Abdullah University of Science and Technology (KAUST)（阿卜杜拉国王科技大学生物医学科学部生物工程项目）； Ningbo Cixi Institute of Biomedical Engineering, Chinese Academy of Sciences（中国科学院宁波慈溪生物医学工程研究所）； Liverpool Centre for Cardiovascular Science, University of Liverpool（利物浦大学利物浦心血管科学中心）

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

AI总结针对生物医学图像分割中几何先验缺乏统一性和泛化性的问题，提出基于Hadwiger定理的全局近凸形状先验，并结合冲突感知目标平衡方法，实现跨器官和模态的即插即用分割。

Comments Provisionally accepted by the 29th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2026). 11 pages, 3 figures, 2 tables

2605.10054 2026-05-12 cs.CV 86%

Explanation-Aware Learning for Enhanced Interpretability in Biomedical Imaging

为提高生物医学影像的可解释性而引入解释感知学习

Zubair Faruqui, Rahul Dubey

机构 * Department of Computer Science, Missouri State University（密苏里州立大学计算机科学系）

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

AI总结本文提出通过在训练中引入解释损失来提升模型对临床相关区域的关注，分析不同解释损失设计对预测性能和空间忠实度的影响，并引入新的评估指标以量化可解释性。

Comments Under review at IEEE Journal of Biomedical and Health Informatics (JBHI)

2509.23442 2025-09-30 eess.IV cs.AI cs.CV cs.LG eess.SP 86%

S$^3$F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network

Md. Saiful Bari Siddiqui, Mohammed Imamul Hassan Bhuiyan

机构 * Department of Computer Science and Engineering, BRAC University（计算机科学与工程系，布拉克大学）； Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology（电气与电子工程系，孟加拉国工程与技术大学）

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

Comments Submitted to IEEE Journal of Biomedical and Health Informatics (JBHI). This preprint includes few additional details not present in the journal submission

2509.09064 2025-09-12 cs.CV 86%

Enhancing 3D Medical Image Understanding with Pretraining Aided by 2D Multimodal Large Language Models

Qiuhui Chen, Xuancheng Yao, Huping Ye, Yi Hong

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

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

Comments Accepted by IEEE Journal of Biomedical and Health Informatics (JBHI)

2507.23272 2025-08-01 cs.CV cs.AI 86%

Towards Affordable Tumor Segmentation and Visualization for 3D Breast MRI Using SAM2

Solha Kang, Eugene Kim, Joris Vankerschaver, Utku Ozbulak

机构 * Center for Biosystems and Biotech Data Science, Ghent University Global Campus, Incheon, Republic of Korea（生物系统与生物技术数据科学中心，格罗宁根大学全球校园，韩国Incheon）； Department of Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium（数学、计算机科学与统计学系，格罗宁根大学，比利时Ghent）； IDLab, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium（IDLab，电子与信息系统系，格罗宁根大学，比利时Ghent）

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

Comments Accepted for publication in the 28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2nd Deep Breast Workshop on AI and Imaging for Diagnostic and Treatment Challenges in Breast Care (DeepBreath), 2025

2406.15699 2024-06-25 cs.CV 86%

Self-Supervised Alignment Learning for Medical Image Segmentation

Haofeng Li, Yiming Ouyang, Xiang Wan

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

Comments Accepted by (ISBI 2024) 2024 IEEE International Symposium on Biomedical Imaging

2404.10965 2024-04-18 eess.IV 86%

IMIL: Interactive Medical Image Learning Framework

Adrit Rao, Andrea Fisher, Ken Chang, John Christopher Panagides, Katherine McNamara, Joon-Young Lee, Oliver Aalami

专题命中医学影像：medical image(title,abstract)；diagnosis(abstract)；radiology(abstract)；分类 eess.IV

Comments CVPR 2024 Workshop on Domain adaptation, Explainability and Fairness in AI for Medical Image Analysis (DEF-AI-MIA)

2011.05791 2021-11-11 stat.ML cs.LG 86%

Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images

Sambuddha Ghosal, Pratik Shah

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

Journal ref Published in Cell Reports Methods 1, 100107, 2021. "A deep-learning toolkit for visualization and interpretation of segmented medical images"

1702.07841 2018-01-17 cs.CV 86%

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Mohsen Ghafoorian, Alireza Mehrtash, Tina Kapur, Nico Karssemeijer, Elena Marchiori, Mehran Pesteie, Charles R. G. Guttmann, Frank-Erik de Leeuw, Clare M. Tempany, Bram van Ginneken, Andriy Fedorov, Purang Abolmaesumi, Bram Platel, William M. Wells

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

Comments 8 pages, 3 figures

Journal ref Medical Image Computing and Computer-Assisted Intervention 2017, Vol 10435, 516-524

2607.14870 2026-07-17 physics.med-ph 新提交 86%

One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy

一适用于所有情况的自适应放射治疗计划智能体：基于每日锥束CT引导的放射治疗基础框架

Shaoyan Pan, Kirk Jon Luca, Yuan Gao, Shansong Wang, Mingzhe Hu, Ryan Sanford, Mojtaba Safari, Justin Roper, Zhen Tian, Tonghe Wang, Xiaofeng Yang

专题命中医学影像：CT(title_cn,summary_cn)

AI总结介绍一适用于所有情况的自适应放射治疗计划智能体，它基于统一基础模型，能从每日锥束CT执行在线自适应计划，自主预测关键组件并设计临床计划，经多数据集评估，其准确性和计划质量与临床方案相当，为放射治疗带来新机遇。

1511.04336 2026-06-04 math.NA cs.NA 86%

Numerical assessment of shearlet-based regularization in ROI tomography

小区域CT重建中基于shearlet的正则化数值评估

Tatiana A. Bubba, Demetrio Labate, Gaetano Zanghirati, Silvia Bonettini

专题命中医学影像：CT(title_cn,summary_cn)

AI总结本文提出基于shearlet正则化的凸优化方法，用于小区域CT重建，证明其对ROI位置不敏感且在小ROI情况下稳定性强。

Comments 13 pages, 30 figures

1602.07049 2026-06-04 math.NA cs.NA 86%

Limited Tomography Reconstruction via Tight Frame and Sinogram Extrapolation

有限数据CT重建 via 紧密框架与sinogram外推

Jae Kyu Choi, Bin Dong, Xiaoqun Zhang

专题命中医学影像：CT(title_cn,summary_cn)

AI总结本文提出利用紧密框架正则化和同时sinogram外推方法，从有限sinogram数据中重建完整CT图像，优于传统稀疏模型方法。

2606.02156 2026-06-02 eess.IV cs.AI cs.CV cs.IR cs.LG 86%

Predicting the risk of colorectal anastomotic leak based on preoperative mapping of the blood supply of the bowel

基于术前肠道血供映射预测结直肠吻合口漏风险

Zahra Tabatabaei, Jon Sporring, Mark Bremholm Ellebæk, Alaa El-Hussuna

机构 * Computer Science Department, Københavns Universitet (KU)（哥本哈根大学计算机科学系）； University of Southern Denmark（南部丹麦大学）； Odense University Hospital（奥登塞大学医院）； OpenSourceResearch Collaboration（开源研究协作）

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

AI总结提出一种基于术前CT影像的AI驱动系统，通过分析血管和组织特征量化吻合口漏风险，并结合内容检索支持临床决策。

2410.09234 2024-10-15 cs.CL 86%

Fine-Tuning In-House Large Language Models to Infer Differential Diagnosis from Radiology Reports

Luoyao Chen, Revant Teotia, Antonio Verdone, Aidan Cardall, Lakshay Tyagi, Yiqiu Shen, Sumit Chopra

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

Comments 10 pages, 2 figures, 4 tables

2409.13038 2024-09-23 cs.AI 86%

HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation

Julián N. Acosta, Xiaoman Zhang, Siddhant Dogra, Hong-Yu Zhou, Seyedmehdi Payabvash, Guido J. Falcone, Eric K. Oermann, Pranav Rajpurkar

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

2008.07588 2024-08-19 eess.IV cs.CV cs.LG stat.ML 86%

Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation

Abhinav Sagar

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

2311.07234 2023-11-14 eess.IV cs.CV cs.LG 86%

Multi-task learning for joint weakly-supervised segmentation and aortic arch anomaly classification in fetal cardiac MRI

Paula Ramirez, Alena Uus, Milou P. M. van Poppel, Irina Grigorescu, Johannes K. Steinweg, David F. A. Lloyd, Kuberan Pushparajah, Andrew P. King, Maria Deprez

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

Comments Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:015

Journal ref Machine.Learning.for.Biomedical.Imaging. 2 (2023)

2307.15872 2023-08-01 eess.IV cs.CV cs.LG 86%

Cross-dimensional transfer learning in medical image segmentation with deep learning

Hicham Messaoudi, Ahror Belaid, Douraied Ben Salem, Pierre-Henri Conze

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

Comments 30 pages, 12 figures, 6 tables, Accepted for publication in the Journal of Medical Image Analysis

Journal ref In Medical Image Analysis (Vol. 88, p. 102868). Elsevier BV (2023)

1910.02923 2021-05-06 cs.LG cs.CV cs.HC eess.IV 86%

A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis

Samuel Budd, Emma C Robinson, Bernhard Kainz

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

Comments Medical Image Analysis Volume 71 2021 https://doi.org/10.1016/j.media.2021.102062

Journal ref Medical Image Analysis, Volume 71, 2021, 102062, ISSN 1361-8415

2004.10734 2021-03-30 eess.IV cs.CV cs.LG 86%

Red-GAN: Attacking class imbalance via conditioned generation. Yet another perspective on medical image synthesis for skin lesion dermoscopy and brain tumor MRI

Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe, Johannes C Paetzold, Anjany Sekuboyina, Florian Kofler, Jana Lipkova, Hongwei Li, Bjoern Menze

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

Journal ref Published in Proceedings of the 3rd edition of Medical Imaging with Deep Learning, Montréal, Canada, PMLR 121, 2020

1. 医学影像 22596 篇

Tackling the Problem of Large Deformations in Deep Learning Based Medical Image Registration Using Displacement Embeddings

MS-Net: Multi-Site Network for Improving Prostate Segmentation with Heterogeneous MRI Data

Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation

Automatic Lumbar Spinal CT Image Segmentation with a Dual Densely Connected U-Net

Dataset Growth in Medical Image Analysis Research

SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis

Coupled-Projection Residual Network for MRI Super-Resolution

Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis

Deep Learning for Automated Medical Image Analysis

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

HadBalance: A Plug-and-Play Unified Global Geometric Prior Framework for Generalizable Biomedical Segmentation

Explanation-Aware Learning for Enhanced Interpretability in Biomedical Imaging

S$^3$F-Net: A Multi-Modal Approach to Medical Image Classification via Spatial-Spectral Summarizer Fusion Network

Enhancing 3D Medical Image Understanding with Pretraining Aided by 2D Multimodal Large Language Models

Towards Affordable Tumor Segmentation and Visualization for 3D Breast MRI Using SAM2

Self-Supervised Alignment Learning for Medical Image Segmentation

IMIL: Interactive Medical Image Learning Framework

Interpretable and synergistic deep learning for visual explanation and statistical estimations of segmentation of disease features from medical images

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy

Numerical assessment of shearlet-based regularization in ROI tomography

Limited Tomography Reconstruction via Tight Frame and Sinogram Extrapolation

Predicting the risk of colorectal anastomotic leak based on preoperative mapping of the blood supply of the bowel

Fine-Tuning In-House Large Language Models to Infer Differential Diagnosis from Radiology Reports

HeadCT-ONE: Enabling Granular and Controllable Automated Evaluation of Head CT Radiology Report Generation

Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation

Multi-task learning for joint weakly-supervised segmentation and aortic arch anomaly classification in fetal cardiac MRI

Cross-dimensional transfer learning in medical image segmentation with deep learning

A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis

Red-GAN: Attacking class imbalance via conditioned generation. Yet another perspective on medical image synthesis for skin lesion dermoscopy and brain tumor MRI