医学 AI

Classification of histopathology images using ConvNets to detect Lupus Nephritis

Akash Gupta, Anirudh Reddy, CV Jawahar, PK Vinod

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、q-bio

Comments Accepted in the 2021 Medical Imaging meets NeurIPS Workshop

Hard Sample Aware Noise Robust Learning for Histopathology Image Classification

Chuang Zhu, Wenkai Chen, Ting Peng, Ying Wang, Mulan Jin

专题命中 病理影像 ：diagnosis(abstract)；分类 cs.CV、cs.LG、q-bio

Comments 14 pages, 20figures, IEEE Transactions on Medical Imaging

Morphomics via Next-generation Electron Microscopy

Raku Son, Kenji Yamazawa, Akiko Oguchi, Mitsuo Suga, Masaru Tamura, Yasuhiro Murakawa, Satoshi Kume

专题命中 病理影像 ：pathology(abstract)；diagnosis(abstract)；分类 q-bio

Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification

Yuan Xue, Jiarong Ye, Qianying Zhou, Rodney Long, Sameer Antani, Zhiyun Xue, Carl Cornwell, Richard Zaino, Keith Cheng, Xiaolei Huang

专题命中 病理影像 ：diagnosis(abstract)；medical image(comments,journal_ref)；分类 cs.CV、eess.IV

Comments Elsevier Medical Image Analysis Best Paper Award runner up. arXiv admin note: substantial text overlap with arXiv:1912.03837

Journal ref Medical Image Analysis 67 (2021): 101816

Pathological Analysis of Blood Cells Using Deep Learning Techniques

Virender Ranga, Shivam Gupta, Priyansh Agrawal, Jyoti Meena

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、q-bio

Comments 6 Page, 3 Table and 6 Figures

Journal ref Recent Advances in Computer Science and Communications(Formerly Recent Patents on Computer Science),04 September,2020, Article ID e140921185564

Towards personalized computer simulations of breast cancer treatment

Alvaro Köhn-Luque, Xiaoran Lai, Arnoldo Frigessi

专题命中 病理影像 ：MRI(abstract)；pathology(abstract)；分类 q-bio

Comments 2 pages, 2 figures, VPH2020 Conference

Unsupervised Learning of Deep-Learned Features from Breast Cancer Images

Sanghoon Lee, Colton Farley, Simon Shim, Yanjun Zhao, Wookjin Choi, Wook-Sung Yoo

专题命中 病理影像 ：diagnosis(abstract)；分类 cs.CV、cs.LG、q-bio

Comments 7 pages for IEEE BIBE

Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection

Khashayar Namdar, Isha Gujrathi, Masoom A. Haider, Farzad Khalvati

专题命中 病理影像 ：MRI(abstract)；分类 cs.CV、cs.LG、q-bio

Comments Accepted for the 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Medical Imaging Meets NEURIPS Workshop

A frame semantic overview of NLP-based information extraction for cancer-related EHR notes

Surabhi Datta, Elmer V Bernstam, Kirk Roberts

专题命中 病理影像 ：diagnosis(abstract)；biomedical(abstract)；分类 q-bio

Comments 2 figures, 4 tables

Chromatin Laser Imaging Reveals Abnormal Nuclear Changes for Early Cancer Detection

Yu-Cheng Chen, Qiushu Chen, Xiaotain Tan, Grace Chen, Ingrid Bergin, Muhammad Nadeem Aslam, Xudong Fan

专题命中 病理影像 ：diagnosis(abstract)；biomedical(abstract)；分类 q-bio

Multi-radial LBP Features as a Tool for Rapid Glomerular Detection and Assessment in Whole Slide Histopathology Images

Olivier Simon, Rabi Yacoub, Sanjay Jain, Pinaki Sarder

专题命中 病理影像 ：pathology(abstract)；diagnosis(abstract)；分类 q-bio

Comments 14 pages, 6 figures. Added scalebars, and for Fig. 3b a clearer example of medulla removal

Utilisation de la substitution sensorielle par électro-stimulation linguale pour la prévention des escarres chez les paraplégiques. Etude préliminaire

Alexandre Moreau-Gaudry, Fabien Robineau, Pierre-Frédéric André, Anne Prince, Pierre Pauget, Jacques Demongeot, Yohan Payan

专题命中 病理影像 ：pathology(abstract)；biomedical(abstract)；分类 q-bio

Journal ref L'escarre 30 (2006) 24-37

Prévention des escarres chez les paraplégiques : une nouvelle approche par électrostimulation linguale

Alexandre Moreau-Gaudry, Anne Prince, Jacques Demongeot, Yohan Payan

专题命中 病理影像 ：pathology(abstract)；biomedical(abstract)；分类 q-bio

Journal ref Actes de la 4ème Conférence Handicap 2006 "Nouvelles Technologies au service de l'homme" (2006) 216-220

Test-Time Instance Selection for Improved Whole Slide Image Analysis

用于改进全切片图像分析的测试时实例选择

Quoc Anh Nguyen, Sunhong Park, Jin Tae Kwak

专题命中 病理影像 ：diagnosis(abstract)；分类 cs.CV、q-bio、eess.IV；medical AI(comments)

AI总结 本研究提出无需训练的即插即用测试时实例选择框架TTIS，融入多视图集成策略，可无缝集成到现有MIL模型，在多个WSI分析基准任务中性能优于或匹配基线模型。

Comments Accepted at The 2nd MICCAI Workshop on Efficient Medical AI (EMA4MICCAI 2026)

Path-GPTOmic: A Balanced Multi-modal Learning Framework for Survival Outcome Prediction

Hongxiao Wang, Yang Yang, Zhuo Zhao, Pengfei Gu, Nishchal Sapkota, Danny Z. Chen

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、q-bio；biomedical(comments)

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

A transductive few-shot learning approach for classification of digital histopathological slides from liver cancer

Aymen Sadraoui, Ségolène Martin, Eliott Barbot, Astrid Laurent-Bellue, Jean-Christophe Pesquet, Catherine Guettier, Ismail Ben Ayed

专题命中 病理影像 ：diagnosis(abstract)；分类 cs.LG、q-bio、eess.IV；biomedical(journal_ref)

Journal ref ISBI 2024 - 21st IEEE International Symposium on Biomedical Imaging, May 2024, Ath{è}nes, Greece

Improving Unsupervised Stain-To-Stain Translation using Self-Supervision and Meta-Learning

Nassim Bouteldja, Barbara Mara Klinkhammer, Tarek Schlaich, Peter Boor, Dorit Merhof

专题命中 病理影像 ：pathology(abstract,comments)；分类 cs.CV、q-bio、eess.IV

Comments Accepted for Journal of Pathology Informatics (JPI), 2022

Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists

Wouter Bulten, Maschenka Balkenhol, Jean-Joël Awoumou Belinga, Américo Brilhante, Aslı Çakır, Xavier Farré, Katerina Geronatsiou, Vincent Molinié, Guilherme Pereira, Paromita Roy, Günter Saile, Paulo Salles, Ewout Schaafsma, Joëlle Tschui, Anne-Marie Vos, Hester van Boven, Robert Vink, Jeroen van der Laak, Christina Hulsbergen-van de Kaa, Geert Litjens

专题命中 病理影像 ：pathology(abstract,journal_ref)；分类 cs.CV、q-bio、eess.IV

Comments 21 pages, 5 figures

Journal ref Modern Pathology, Available online 5 August 2020

4$π$ Planning for the Reduction of Predicted Hematologic Toxicity Risk in Cervical Cancer Radiotherapy

用于降低宫颈癌放疗中预测血液学毒性风险的4π计划

Haotian Feng, Yan Kong, Qifan Xu, Ke Sheng

专题命中 病理影像 ：CT(abstract,abstract_cn)

AI总结 该研究针对宫颈癌共面放疗的血液学毒性风险，用114例患者数据训练模型，发现4π非共面放疗可降低骨髓等剂量，使预测HT风险降23%，为减少该毒性提供了新方案。

Retrieval-Augmented Vision Foundation Models for Robust Leukemia Cell Classification across Multiple Microscopy Datasets

用于跨多个显微镜数据集实现稳健白血病细胞分类的检索增强视觉基础模型

Carlos Zamora, Hiram Zuniga, Ulises Orozco-Rosas, Kenia Picos

专题命中 病理影像 ：biomedical(abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 本研究提出基于预训练视觉基础模型的两阶段检索增强框架，经多数据集测试，可实现跨异构数据集的稳健白血病细胞分类，为解决领域偏移问题提供低成本替代方案。

Comments Accepted at SPIE Optics + Photonics 2026 for oral presentation. 23 pages, 12 figures, 9 tables

Dynamic Image-Informed Selection of Biomechanical Tumor Growth Models

生物力学肿瘤生长模型的动态图像信息选择

Abdullah Al Noman, Pratyush Kumar Singh, David A Hormuth, Danial Faghihi

专题命中 病理影像 ：MRI(abstract,abstract_cn)

AI总结 研究胶质母细胞瘤进展中机械相互作用对其的影响。通过引入序贯贝叶斯推理和动态模型选择框架，利用纵向小鼠磁共振成像数据校准生物力学肿瘤生长模型参数，比较不同模型，得出机械耦合模型更优及应依个体评估本构假设的结论。

Reducing Redundancy in Whole-Slide Image Patching for Scalable Indexing and Retrieval

减少全切片图像分块冗余以实现可扩展索引与检索

Jialiang Geng, Ghazal Alabtah, Saghir Alfasly, Wataru Uegami, H. R. Tizhoosh

机构 * KIMIA Lab Dept. of Artificial Intelligence & Informatics（KIMIA实验室 人工智能与信息学系） 纠错

专题命中 病理影像 ：clinical AI(abstract)；pathology(abstract)

AI总结 提出ARReST框架，通过识别并剪除跨类别判别贡献小的对立块，在保持检索精度的同时显著压缩WSI索引存储（3%-60%），实现可扩展、低成本的病理图像检索。

Ablation Study of a Fairness Auditing Agentic System for Bias Mitigation in Early-Onset Colorectal Cancer Detection

公平性审计代理系统在早发性结直肠癌检测中缓解偏见的消融研究

Amalia Ionescu, Jose Guadalupe Hernandez, Jui-Hsuan Chang, Emily F. Wong, Paul Wang, Jason H. Moore, Tiffani J. Bright

专题命中 病理影像 ：clinical AI(abstract)；biomedical(abstract)

AI总结 提出双代理架构（领域专家代理+公平性顾问代理），通过消融实验比较不同配置下大语言模型在公平性审计中的表现，发现带RAG的代理系统在识别差异方面语义相似度最高。

DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole-Slide Image Survival Prediction

DPsurv: 双原型证据融合用于不确定性感知和可解释的全切片图像生存预测

Yucheng Xing, Ling Huang, Jingying Ma, Ruping Hong, Jiangdong Qiu, Pei Liu, Kai He, Huazhu Fu, Mengling Feng

机构 * National University of Singapore ； National University of Singapore Guangzhou Research Translation ； Innovation Institute ； Imperial College London ； Peking Union Medical College Hospital, Chinese Academy of Medical Sciences \& Peking Union Medical College ； Hunan University ； Institute of High Performance Computing, Agency for Science, Technology ； Research (A STAR) 纠错

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 提出DPsurv双原型证据融合网络，通过不确定性感知的生存区间预测和基于补丁原型分配图、组件原型及组件级相对风险聚合的可解释性，在五个公开数据集上取得最佳一致性指数和积分Brier分数。

Detecting Breast Carcinoma Metastasis on Whole-Slide Images by Partially Subsampled Multiple Instance Learning

通过部分下采样多实例学习检测乳腺癌转移于全滑动图像

Baichen Yu, Xuetong Li, Jing Zhou, Hansheng Wang

专题命中 病理影像 ：pathology(abstract)；diagnosis(abstract)

AI总结 本文提出基于高斯混合的多实例学习框架，通过部分下采样实例来提高全滑动图像分析的效率和准确性，验证了其在乳腺癌转移预测中的有效性。

Development, Evaluation, and Deployment of a Multi-Agent System for Thoracic Tumor Board

胸腔肿瘤板的多智能体系统开发、评估与部署

Tim Ellis-Caleo, Timothy Keyes, Nerissa Ambers, Faraah Bekheet, Wen-wai Yim, Nikesh Kotecha, Nigam H. Shah, Joel Neal

机构 * Division of Oncology, Department of Medicine, Stanford University School of Medicine（斯坦福大学医学院肿瘤学部） ； Technology and Digital Solutions, Stanford Health Care（斯坦福健康医疗技术与数字解决方案部） ； Department of Biomedical Data Science, Stanford University School of Medicine（斯坦福大学医学院生物医学数据科学部） ； Nursing Informatics, Stanford Health Care（斯坦福健康护理信息学部） ； Department of Medicine, Stanford University School of Medicine（斯坦福大学医学院医学部） ； Microsoft AI, Redmond, WA（微软人工智能，西雅图） ； Stanford Cancer Institute, Palo Alto, CA（斯坦福癌症研究所） 纠错

专题命中 病理影像 ：pathology(abstract)；radiology(abstract)

AI总结 本文提出了一种多智能体系统，用于生成胸腔肿瘤病例摘要，以提高讨论效率和准确性，并验证了LLM在事实评分中的应用。

Comments 64 pages, 14 figures

UNIStainNet: Foundation-Model-Guided Virtual Staining of H&E to IHC

UNIStainNet：基于基础模型的虚拟染色：H&E到IHC

Jillur Rahman Saurav, Thuong Le Hoai Pham, Pritam Mukherjee, Paul Yi, Brent A. Orr, Jacob M. Luber

机构 * University of Texas at Arlington（德克萨斯理工大学） ； St. Jude Children’s Research Hospital（圣 Jude 儿童研究医院） 纠错

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 UNIStainNet通过结合基础模型生成的密集空间标记，提升H&E到IHC的虚拟染色效果，实现多标记同时处理，并在MIST和BCI数据集上取得最佳分布度指标。

Inferring Clinically Relevant Molecular Subtypes of Pancreatic Cancer from Routine Histopathology Using Deep Learning

通过深度学习从常规组织病理学切片推断胰腺癌的临床相关分子亚型

Abdul Rehman Akbar, Alejandro Levya, Ashwini Esnakula, Elshad Hasanov, Anne Noonan, Lingbin Meng, Susan Tsai, Vaibhav Sahai, Midhun Malla, Sarbajit Mukherjee, Upender Manne, Anil Parwani, Wei Chen, Ashish Manne, Muhammad Khalid Khan Niazi

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 PanSubNet通过深度学习从常规H&E染色切片预测胰腺癌分子亚型，提供可解释的临床应用工具。

Clinical-Injection Transformer with Domain-Adapted MAE for Lupus Nephritis Prognosis Prediction

具有领域适应MAE的临床注射变换器用于系统性红斑狼疮肾炎的预后预测

Yuewen Huang, Zhitao Ye, Guangnan Feng, Fudan Zheng, Xia Gao, Yutong Lu

机构 * Sun Yat-sen University Department of Nephrology, Guangzhou Women ； Children's Medical Center, Guangzhou Medical University, Guangzhou, China 纠错

专题命中 病理影像 ：pathology(abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 本研究提出了一种多模态计算病理学框架，利用临床数据和常规染色活检，通过临床注射变换器和领域适应MAE实现儿童系统性红斑狼疮肾炎预后预测的高准确率。

Deep Learning for Dermatology: An Innovative Framework for Approaching Precise Skin Cancer Detection

深度学习在皮肤科中的应用：一种用于精确皮肤癌检测的创新框架

Mohammad Tahmid Noor, B. M. Shahria Alam, Tasmiah Rahman Orpa, Shaila Afroz Anika, Mahjabin Tasnim Samiha, Fahad Ahammed

专题命中 病理影像 ：diagnosis(abstract)；分类 cs.CV、cs.LG、eess.IV

AI总结 本文提出了一种创新的深度学习框架，用于精确检测皮肤癌，通过评估VGG16和DenseNet201模型的准确性与效率，以提高皮肤科诊断的早期检测和工作效率。

Comments 6 pages, 9 figures, this is the author's accepted manuscript of a paper accepted for publication in the Proceedings of the 16th International IEEE Conference on Computing, Communication and Networking Technologies (ICCCNT 2025). The final published version will be available via IEEE Xplore