医学 AI

Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression

Daniele Ravi, Daniel C. Alexander, Neil P. Oxtoby

专题命中 医学数据与评测 ：MRI(abstract)；分类 cs.CV、eess.IV

Comments Paper accepted for MICCAI 2019

Customized OCT images compression scheme with deep neural network

Pengfei Guo, Dawei Li, Xingde Li

专题命中 医学数据与评测 ：medical image(abstract)；分类 cs.CV、eess.IV

Comments One of author disagrees to release this paper at Arxiv

LANTERN: learn analysis transform network for dynamic magnetic resonance imaging with small dataset

Shanshan Wang, Yanxia Chen, Taohui Xiao, Ziwen Ke, Qiegen Liu, Hairong Zheng

专题命中 医学数据与评测 ：MRI(abstract)；分类 cs.CV、eess.IV

Transfer Learning with intelligent training data selection for prediction of Alzheimer's Disease

Naimul Mefraz Khan, Marcia Hon, Nabila Abraham

专题命中 医学数据与评测 ：MRI(abstract)；分类 cs.CV、cs.LG

Comments Accepted to IEEE Access

An Objective Evaluation Metric for image fusion based on Del Operator

Ali A. Kiaei, Hassan Khotanlou, Mahdi Abbasi, Paniz Kiaei, Yasin Bhrouzi

专题命中 医学数据与评测 ：medical image(abstract)；分类 cs.CV、eess.IV

Comments 22 pages, 14 Figures

Histopathologic Image Processing: A Review

Jonathan de Matos, Alceu de Souza Britto, Luiz E. S. Oliveira, Alessandro L. Koerich

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.CV、cs.LG

Age prediction using a large chest X-ray dataset

Alexandros Karargyris, Satyananda Kashyap, Joy T Wu, Arjun Sharma, Mehdi Moradi, Tanveer Syeda-Mahmood

专题命中 医学数据与评测 ：medical image(abstract)；分类 cs.CV、cs.LG

Comments Presented at SPIE Medical Imaging Conference, San Diego, 2019

Classifying Mammographic Breast Density by Residual Learning

Jingxu Xu, Cheng Li, Yongjin Zhou, Lisha Mou, Hairong Zheng, Shanshan Wang

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.CV、cs.LG

ChronoNet: A Deep Recurrent Neural Network for Abnormal EEG Identification

Subhrajit Roy, Isabell Kiral-Kornek, Stefan Harrer

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.LG、eess.SP

Comments 8 pages, 2 figures, 2 tables

A Benchmark for Hallucination Detection in VLMs for Gastrointestinal Endoscopy

胃肠内窥镜中视觉语言模型幻觉检测的基准测试

Aminu Lawal, Niyoj Oli, Sachin Acharya, Prashnna Gyawali, Maria Carmen Romano, Binod Bhattarai

机构 * University of Aberdeen（阿伯丁大学） ； Nepal Applied Mathematics and Informatics Institute for Research（尼泊尔应用数学与信息学研究所） ； West Virginia University（西弗吉尼亚大学） 纠错

专题命中 医学数据与评测 ：radiology(abstract)；分类 cs.CV；medical image(comments)

AI总结 针对胃肠内窥镜领域，在Gut-VLM数据集上基准测试九种幻觉检测方法，发现白盒方法ReXTrust在所有五个视觉语言模型上AUC最高，平均领先19.5点。

Comments Accepted at the Medical Image Understanding and Analysis (MIUA) 2026 conference

MuellerPT: Decomposition Driven Pretraining for Dense Learning in Mueller Polarimetry

MuellerPT: 穆勒偏振测量中密集学习的分解驱动预训练

Adam Tlemsani, Yingdian Li, Maxime Giot, Naim Slim, Christopher J. Peters, Abhijeet Ghosh, Daniel S. Elson

机构 * Department of Computing, Imperial College London（帝国理工学院计算机系） ； Hamlyn Centre for Robotic Surgery, Imperial College London（帝国理工学院机器人外科中心） ； Department of Surgery and Cancer, Imperial College London（帝国理工学院外科与癌症系） ； Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences（中国科学院西安光学精密机械研究所） ； University of Chinese Academy of Sciences（中国科学院大学） 纠错

专题命中 医学数据与评测 ：biomedical(abstract)；分类 cs.CV；medical image(comments)

AI总结 提出MuellerPT，一种通过预测Lu-Chipman分解图进行物理引导预训练的方法，在少样本分割和分类任务中显著提升标签效率和跨样本泛化能力。

Comments Accepted to 29th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2026)

A COCO-Formatted Instance-Level Dataset for Plasmodium Falciparum Detection in Giemsa-Stained Blood Smears

Frauke Wilm, Luis Carlos Rivera Monroy, Mathias Öttl, Lukas Mürdter, Leonid Mill, Andreas Maier

机构 * MIRA Vision Microscopy GmbH（MIRA视觉显微镜 GmbH） ； Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg（模式识别实验室，计算机科学系，弗赖堡-艾尔兰根-纽伦堡大学） 纠错

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.CV；biomedical(journal_ref)

Comments 7 pages, 4 figures, 2 tables, accepted at MICCAI 2025 Open Data

Journal ref Machine Learning for Biomedical Imaging (MELBA), MICCAI Open Data Special Issue, 2025

AbdomenAtlas: A Large-Scale, Detailed-Annotated, & Multi-Center Dataset for Efficient Transfer Learning and Open Algorithmic Benchmarking

Wenxuan Li, Chongyu Qu, Xiaoxi Chen, Pedro R. A. S. Bassi, Yijia Shi, Yuxiang Lai, Qian Yu, Huimin Xue, Yixiong Chen, Xiaorui Lin, Yutong Tang, Yining Cao, Haoqi Han, Zheyuan Zhang, Jiawei Liu, Tiezheng Zhang, Yujiu Ma, Jincheng Wang, Guang Zhang, Alan Yuille, Zongwei Zhou

机构 * Department of Computer Science, Johns Hopkins University ； Department of Bioengineering, University of Illinois Urbana-Champaign ； Alma Mater Studiorum - University of Bologna ； Center for Biomolecular Nanotechnologies, Istituto Italiano di Tecnologia ； LKS Faculty of Medicine, The University of Hong Kong ； Department of Computer Science, Southeast University ； Department of Radiology, Southeast University Zhongda Hospital ； Department of Medical Oncology, The First Hospital of China Medical University ； The Second Clinical College, China Medical University ； Department of Mechanical Engineering ； the Laboratory of Computational Sensing ； Robotics, Johns Hopkins University ； Center of Reproductive Medicine, Department of Obstetrics ； Gynecology, Shengjing Hospital of China Medical University ； Radiology Department, the First Affiliated Hospital, School of Medicine, Zhejiang University ； Department of Health Management, The First Affiliated Hospital of Shandong First Medical University \& Shandong Provincial Qianfoshan Hospital ； Shandong Engineering Research Center of Health Management ； Shandong Institute of Health Management 纠错

专题命中 医学数据与评测 ：CT(abstract)；分类 cs.CV；medical image(comments)

Comments Published in Medical Image Analysis

The Developing Human Connectome Project: A Fast Deep Learning-based Pipeline for Neonatal Cortical Surface Reconstruction

Qiang Ma, Kaili Liang, Liu Li, Saga Masui, Yourong Guo, Chiara Nosarti, Emma C. Robinson, Bernhard Kainz, Daniel Rueckert

专题命中 医学数据与评测 ：MRI(abstract)；分类 eess.IV；medical image(comments)

Comments Accepted by Medical Image Analysis

Incorporation of Eye-Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-rays: A Randomized Controlled Clinical Trial

Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Stanford Martinez, Angel Brisco, Nicholas Czarnek, Adel Alaeddini, Jeffrey R. Mock, Edward J. Golob, Kal L. Clark

专题命中 医学数据与评测 ：radiology(abstract,comments)；分类 eess.IV

Comments Submitted for Review in the Journal of the American College of Radiology (JACR)

Discrimination of Radiologists Utilizing Eye-Tracking Technology and Machine Learning: A Case Study

Stanford Martinez, Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Kal L. Clark, Adel Alaeddini, Nicholas Czarnek, Aarushi Aggarwal, Sahra Emamzadeh, Jeffrey R. Mock, Edward J. Golob

专题命中 医学数据与评测 ：radiology(abstract)；分类 cs.CV；biomedical(comments)

Comments Submitting for Review in "IEEE Journal of Biomedical and Health Informatics"

Leveraging Unlabelled Data in Multiple-Instance Learning Problems for Improved Detection of Parkinsonian Tremor in Free-Living Conditions

Alexandros Papadopoulos, Anastasios Delopoulos

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.LG；biomedical(comments)

Comments A. Papadopoulos and A. Delopoulos, "Leveraging Unlabelled Data in Multiple-Instance Learning Problems for Improved Detection of Parkinsonian Tremor in Free-Living Conditions," in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2023.3267095

Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark

Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen, Xiaoqian Jiang, Yejin Kim

专题命中 医学数据与评测 ：biomedical(abstract,journal_ref)；分类 cs.LG

Comments 52 pages, 8 figures

Journal ref Journal of Biomedical Informatics (2022): 104256

Unsupervised inter-frame motion correction for whole-body dynamic PET using convolutional long short-term memory in a convolutional neural network

Xueqi Guo, Bo Zhou, David Pigg, Bruce Spottiswoode, Michael E. Casey, Chi Liu, Nicha C. Dvornek

专题命中 医学数据与评测 ：分类 cs.CV、cs.LG、eess.IV；medical image(comments)

Comments Preprint submitted to Medical Image Analysis

Federated Learning Algorithms for Generalized Mixed-effects Model (GLMM) on Horizontally Partitioned Data from Distributed Sources

Wentao Li, Jiayi Tong, Md. Monowar Anjum, Noman Mohammed, Yong Chen, Xiaoqian Jiang

专题命中 医学数据与评测 ：biomedical(abstract,comments)；分类 cs.LG

Comments 19 pages, 5 figures, submitted to Journal of Biomedical Informatics

Analysis Towards Classification of Infection and Ischaemia of Diabetic Foot Ulcers

Moi Hoon Yap, Bill Cassidy, Joseph M. Pappachan, Claire O'Shea, David Gillespie, Neil Reeves

专题命中 医学数据与评测 ：pathology(abstract)；分类 cs.CV；biomedical(journal_ref)

Comments 4 pages, 6 figures and 3 tables

Journal ref Conference: 2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)

Atrial Fibrillation Detection Using Deep Features and Convolutional Networks

Sara Ross-Howe, H. R. Tizhoosh

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.LG；biomedical(comments)

Comments Accepted for publication in the IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2019)

MS-MLB: An Open Machine Learning Benchmark for Blood-Based MS Classification

MS-MLB：一个用于血液基质-MS分类的开源机器学习基准

Adam Simson, Ankush Dutta, Quang Bui

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.LG、q-bio

AI总结 该研究提出首个开源MS分类基准MS-MLB，基于GSE17048全血RNA数据，用控制数据泄露的流程评估算法，梯度提升在留存集表现最优，内置外部模型提交路径，仅用于研究比较。

Batch effects can impair federated learning in multi-center omics studies

批次效应可能会损害多中心组学研究中的联邦学习

Yuliya Burankova, Julian Klemm, Jens J. G. Lohmann, Anne Hartebrodt, Ahmad Taheri, Niklas Probul, Jan Baumbach, Olga Zolotareva

机构 * Institute for Computational Systems Biomedicine, University of Hamburg（汉堡大学计算系统生物医学研究所） ； Chair of Proteomics and Bioanalytics, TUM School of Life Sciences, Technical University of Munich（慕尼黑技术大学生命科学学院蛋白质组学与生物分析系） ； Department of Mathematics and Computer Science, University of Southern Denmark（丹麦南部大学数学与计算机科学系） ； Biomedical Network Science Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg（埃尔兰根-纽伦堡大学生物医学网络科学实验室） ； Data Science in Systems Biology, TUM School of Life Sciences, Technical University of Munich（慕尼黑技术大学生命科学学院系统生物学数据科学） ； Institute of Clinical Molecular Biology (IKMB), Kiel University and University Medical Center Schleswig-Holstein（基尔大学与石勒苏益格-荷尔斯泰因大学医学中心临床分子生物学研究所） 纠错

专题命中 医学数据与评测 ：biomedical(abstract)；分类 cs.LG、q-bio

AI总结 研究多中心组学研究中未校正批次效应影响联邦学习的问题，用四个数据集和两种算法评估，结果表明需校正，还介绍fedRBE实现隐私保护批次效应校正。

Comments The first two authors listed are joint first authors. The last two authors listed are joint last authors. 19 pages, 4 figures, 1 table, supplementary information

Performance and Interpretability of Convolutional, Transformer, and Hybrid Deep Learning Models in Colorectal Histology Classification

卷积、Transformer和混合深度学习模型在结直肠组织学分类中的性能与可解释性

Reza Bozorgpour

机构 * College of Engineering & Applied Science, Department of Biomedical Engineering, University of Wisconsin-Milwaukee（工程与应用科学学院生物医学工程系，威斯康星大学密尔沃基分校） 纠错

专题命中 医学数据与评测 ：pathology(abstract)；分类 cs.CV、q-bio

AI总结 本研究系统比较了12种预训练CNN、Transformer和混合架构在结直肠组织病理学分类中的性能，发现EVA-02和ViT-B/16表现最佳，而现代CNN在准确率与模型复杂度间取得良好平衡。

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity

HR-VILAGE-3K3M：用于系统免疫学的人类呼吸道病毒免疫纵向基因表达数据集

Xuejun Sun, Yiran Song, Xiaochen Zhou, Ruilie Cai, Yu Zhang, Xinyi Li, Rui Peng, Jialiu Xie, Yuanyuan Yan, Muyao Tang, Prem Lakshmanane, Baiming Zou, James S. Hagood, Raymond J. Pickles, Didong Li, Fei Zou, Xiaojing Zheng

机构 * Department of Biostatistics University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校生物统计学系） ； Department of Epidemiology and Biostatistics University of South Carolina（南卡罗来纳大学流行病学与生物统计学系） ； Department of Pediatrics University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校儿科系） ； Department of Microbiology and Immunology University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校微生物学与免疫学系） 纠错

专题命中 医学数据与评测 ：pathology(abstract)；分类 cs.LG、q-bio

AI总结 为解决呼吸道病毒感染研究中转录组数据分散且处理不一致的问题，构建了包含3178名受试者、66项研究的HR-VILAGE-3K3M数据集，整合了疫苗接种、病毒接种和混合暴露的批量及单细胞转录组数据，并进行了统一的预处理和质量控制，以支持生物标志物发现、免疫机制研究和分析方法开发。

ViroBench: Benchmarking Nucleotide Foundation Models on Viral Genomics Tasks

ViroBench：病毒基因组学任务中的核苷酸基础模型基准测试

Dongxin Ye, Fang Hu, Han Hu, Shu Hu, Yang Tan, Wanli Ouyang, Stan Z. Li, Jie Cui, Nanqing Dong

机构 * Shanghai Innovation Institute Shanghai China（深圳河套学院） ； University of Electronic Science ； Fudan University Shanghai China ； Shanghai Artificial Intelligence Laboratory Shanghai China ； Institute of Infection ； Health Fudan University Shanghai China ； Shanghai Sci-Tech Inno Center for Infection \& Immunity Shanghai China ； Shanghai Jiao Tong University Shanghai China ； Shenzhen Loop Area Institute Shenzhen China ； Chinese University of Hong Kong Hong Kong China ； Westlake University Hangzhou China ； Shanghai Innovation Institute ； Fudan University ； Shanghai Artificial Intelligence Laboratory ； Shanghai Sci-Tech Inno Center for Infection \& Immunity ； Shanghai Jiao Tong University ； Shenzhen Loop Area Institute ； Chinese University of Hong Kong ； Westlake University 纠错

专题命中 医学数据与评测 ：biomedical(abstract)；分类 cs.LG、q-bio

AI总结 提出首个针对病毒基因组学的综合基准ViroBench，评估66个核苷酸基础模型在生物学理解和潜在生物安全风险上的表现，发现模型在系统发育和时间偏移下性能下降，生成任务中统计似然与生物功能有效性脱钩，且预训练数据的分类多样性比参数规模更重要。

Comments 42 pages,15 figures

Impact of automatic speech recognition quality on Alzheimer's disease detection from spontaneous speech: a reproducible benchmark study with lexical modeling and statistical validation

自动语音识别质量对自发语音中阿尔茨海默病检测的影响：基于词汇建模和统计验证的可重复基准研究

Himadri S Samanta

机构 * Independent Researcher, Austin, Texas, USA（独立研究者，得克萨斯州奥斯汀） 纠错

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.LG、q-bio

AI总结 本文研究了自动语音识别质量对阿尔茨海默病检测的影响，通过词汇特征和统计验证，发现高质量ASR可提升分类性能，强调ASR选择在临床语音AI系统中的关键作用。

Comments 22 pages, 7 figures

U-FedTomAtt: Ultra-lightweight Federated Learning with Attention for Tomato Disease Recognition

U-FedTomAtt：轻量级联邦学习与注意力机制用于番茄疾病识别

Romiyal George, Sathiyamohan Nishankar, Selvarajah Thuseethan, Chathrie Wimalasooriya, Yakub Sebastian, Roshan G. Ragel, Zhongwei Liang

机构 * Department of Computer Engineering, University of Peradeniya（珀德尼亚大学计算机工程系） ； Faculty of Science and Technology, Charles Darwin University（查尔斯达尔文大学科学与技术学院） ； Canadian Institute for Cybersecurity, University of New Brunswick（新不伦瑞克大学加拿大网络安全研究所） ； School of Mechanical and Electrical Engineering, Guangzhou University（广州大学机械与电子工程学院） 纠错

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.LG、q-bio

AI总结 U-FedTomAtt提出一种轻量级联邦学习框架，结合注意力机制，用于在资源受限环境下识别番茄疾病，实现了高准确率和低计算开销。

Comments 10 pages and 4 figures

Benchmarking Class Activation Map Methods for Explainable Brain Hemorrhage Classification on Hemorica Dataset

在Hemorica数据集上基于类激活图方法的可解释性脑出血分类基准测试

Z. Rafati, M. Hoseyni, J. Khoramdel, A. Nikoofard

机构 * Faculty of Computer Engineering, K. N. Toosi University of Technology（计算机工程学院，K.N.托菲大学） ； Faculty of Electrical Engineering, K. N. Toosi University of Technology（电气工程学院，K.N.托菲大学） ； Faculty of Mechanical Engineering, Tarbiat Modares University（机械工程学院，塔里比亚特莫达res大学） 纠错

专题命中 医学数据与评测 ：diagnosis(abstract)；分类 cs.CV、q-bio

AI总结 本研究通过在Hemorica数据集上评估九种CAM算法，发现AblationCAM在像素级Dice和IoU指标上表现最佳，为脑出血分类的可解释性提供了新的基准。