医学 AI

An End-to-end Pipeline for 3D Slide-wise Multi-stain Renal Pathology Registration

Peize Li, Ruining Deng, Yuankai Huo

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

Comments 6 pages, 4 figures

Journal ref Proceedings Volume Medical Imaging 2023: Digital and Computational Pathology, 124710F (2023)

Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information

Matloob Khushi, Georgina Edwards, Diego Alonso de Marcos, Jane E Carpenter, J Dinny Graham, Christine L Clarke

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

Journal ref Diagnostic Pathology volume 8, Article number: 22 (2013)

Multimodal fusion of imaging and genomics for lung cancer recurrence prediction

Vaishnavi Subramanian, Minh N. Do, Tanveer Syeda-Mahmood

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

Comments Accepted for presentation at International Symposium on Biomedical Imaging (ISBI) 2020 (Iowa City). 5 pages, last page references

Morphology-Aware Implicit Super-Resolution Network for Pathological Images

面向病理图像的形态感知隐式超分辨率网络

Jiaming Liang, QiHui Han, Haolin Chen, Chengxin Ye, Jiawen Liu, Jiazhou Chen, Xiaoqi Sheng, Hongmin Cai

专题命中 病理影像 ：pathology(abstract,abstract_cn)；diagnosis(abstract)；分类 cs.CV

AI总结 针对现有超分辨率方法难以保留病理图像细胞形态的问题，本文提出Morph-ISR框架，在TCGA等数据集上实现最优的LPIPS等指标，可高效保留诊断相关细节并支持边缘部署。

KOAL: Knowledge-Driven Prostate Cancer Grading with Ordinal-Aware Learning

KOAL：基于序数感知学习的知识驱动前列腺癌分级

Zheng Guo, Jiaqi Cui, Haocheng Xiong, Jize Han, Bo Liu, Qianwen Zhang, Rui Chen, Yan Wang

机构 * School of Computer Science, Sichuan University（四川大学计算机学院） ； China Mobile (Suzhou) Software Technology Company Limited（中国移动（苏州）软件技术有限公司） ； Shanghai Changhai Hospital, Naval Medical University（上海长海医院，海军医学大学） ； Renji Hospital, Shanghai Jiao Tong University School of Medicine（仁济医院，上海交通大学医学院） 纠错

专题命中 病理影像 ：MRI(abstract)；pathology(abstract)；radiology(abstract)；分类 cs.CV

AI总结 研究利用mpMRI无创预测前列腺癌GGG的问题，提出KOAL框架，含临床上下文调制、知识引导原型对齐和分层序数感知约束三个模块，实验证明该框架优于现有方法，提升了前列腺癌GGG预测准确性。

Comments 10 pages, 2 figures, 2 tables. Accepted at MICCAI 2026. This is the submitted version prior to peer review. The final authenticated version will be available on SpringerLink

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules

训练集增强与生物学感知的谐波化改善不确定肺结节中肺癌预测的影像组学模型

Claire Huchthausen, Menglin Shi, Gabriel L. A. de Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

机构 * Department of Radiation Oncology, University of Virginia School of Medicine（弗吉尼亚大学医学院放射肿瘤学系） ； Department of Physics, University of Virginia（弗吉尼亚大学物理系） ； Department of Physics, Massachusetts Institute of Technology（麻省理工学院物理系） ； Department of Biomedical Engineering, Northwestern University（西北大学生物医学工程系） ； Department of Radiation Oncology, University of Virginia（弗吉尼亚大学放射肿瘤学系） ； Old Dominion University（旧 Dominion 大学） 纠错

专题命中 病理影像 ：CT(abstract,abstract_cn)；diagnosis(abstract)；分类 cs.CV

AI总结 针对早期肺结节恶性率低和图像采集差异问题，通过加入后期结节扩充训练集，并采用生物学感知的谐波化方法校正采集效应，显著提升了影像组学模型的预测性能（ROC-AUC 0.74）。

Comments 22 pages, 5 figures, plus supplemental material; updated with the accepted version of the manuscript

BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routine

BreastGPT: 面向乳腺癌临床全流程的多模态大语言模型

Yang Liu, Jiajin Zhang, Danyang Tu, Yaojun Hu, Jiao Qu, Jiuyu Zhang, Yu Shi, Wei Fang, Shi Gu, Ling Zhang, Yingda Xia

机构 * DAMO Academy, Alibaba Group（阿里巴巴集团 DAMO 院） ； Zhejiang University（浙江大学） ； Hupan Lab（华潘实验室） ； West China Hospital（西京医院） ； China Medical University（中国医科大学） 纠错

专题命中 病理影像 ：pathology(abstract)；diagnosis(abstract)；radiology(abstract)；分类 cs.CV

AI总结 提出BreastGPT多模态大语言模型，通过构建工作流对齐的指令语料库BreastStage和双分支视觉编码器，实现乳腺癌筛查、诊断和治疗规划全流程的多模态推理，在BreastStage-Bench上取得75.66%封闭式准确率和89.92%开放式得分。

an interpretable vision transformer framework for automated brain tumor classification

一种可解释的视觉变换器框架用于自动脑肿瘤分类

Chinedu Emmanuel Mbonu, Tochukwu Sunday Belonwu, Okwuchukwu Ejike Chukwuogo, Kenechukwu Sylvanus Anigbogu

机构 * Department of Computer Science, Nazarbayev University（纳扎尔巴耶夫大学计算机科学系） ； Department of Computer Science, Nnamdi Azikiwe University（恩内迪·阿齐基韦大学计算机科学系） 纠错

专题命中 病理影像 ：MRI(abstract,abstract_cn)；diagnosis(abstract)；分类 cs.CV

AI总结 本文提出一种基于视觉变换器的框架，用于自动分类四种脑肿瘤类型，通过预训练和增强技术提升分类准确率与可解释性。

Comments 9 pages, 6 figures

Deep Learning-Based Computer Vision Models for Early Cancer Detection Using Multimodal Medical Imaging and Radiogenomic Integration Frameworks

基于深度学习的计算机视觉模型用于多模态医学影像和放射基因组整合框架中的早期癌症检测

Emmanuella Avwerosuoghene Oghenekaro

专题命中 病理影像 ：MRI(abstract)；CT(abstract)；diagnosis(abstract)；分类 cs.CV

AI总结 本文提出基于深度学习的计算机视觉模型，结合多模态医学影像和放射基因组学，用于早期癌症检测，提升肿瘤基因型预测和治疗抗性分析能力。

Journal ref International Journal of Computer Applications Technology and Research, vol. 14, no. 11, pp. 1-14, 2025

Tumor Synthesis conditioned on Radiomics

Jonghun Kim, Inye Na, Eun Sook Ko, Hyunjin Park

机构 * Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea（延世大学电气与计算机工程系） ； Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Suwon, Korea（延世大学医学院放射科与成像科学中心） 纠错

专题命中 病理影像 ：medical image(abstract)；MRI(abstract)；CT(abstract)；分类 cs.CV

Comments WACV'25

Application of NotebookLM, a Large Language Model with Retrieval-Augmented Generation, for Lung Cancer Staging

Ryota Tozuka, Hisashi Johno, Akitomo Amakawa, Junichi Sato, Mizuki Muto, Shoichiro Seki, Atsushi Komaba, Hiroshi Onishi

专题命中 病理影像 ：CT(abstract)；diagnosis(abstract)；radiology(abstract)；分类 cs.LG

Comments 9 pages, 5 figures, 1 table, 3 ancillary files

$M^{2}$Fusion: Bayesian-based Multimodal Multi-level Fusion on Colorectal Cancer Microsatellite Instability Prediction

Quan Liu, Jiawen Yao, Lisha Yao, Xin Chen, Jingren Zhou, Le Lu, Ling Zhang, Zaiyi Liu, Yuankai Huo

专题命中 病理影像 ：CT(abstract)；pathology(abstract)；radiology(abstract)；分类 cs.CV

Ensemble of CNN classifiers using Sugeno Fuzzy Integral Technique for Cervical Cytology Image Classification

Rohit Kundu, Hritam Basak, Akhil Koilada, Soham Chattopadhyay, Sukanta Chakraborty, Nibaran Das

专题命中 病理影像 ：medical image(abstract)；diagnosis(abstract)；biomedical(abstract)；分类 cs.CV

Comments 16 pages

Multiscale Detection of Cancerous Tissue in High Resolution Slide Scans

Qingchao Zhang, Coy D. Heldermon, Corey Toler-Franklin

专题命中 病理影像 ：medical image(abstract)；pathology(abstract)；biomedical(abstract)；分类 cs.CV

Comments 14 pages, 7 figures, 2 tables

Journal ref Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science

Cancer image classification based on DenseNet model

Ziliang Zhong, Muhang Zheng, Huafeng Mai, Jianan Zhao, Xinyi Liu

专题命中 病理影像 ：medical image(abstract)；pathology(abstract)；diagnosis(abstract)；分类 cs.CV

Journal ref 2004-present Journal of Physics: Conference Series

From Human Mesenchymal Stromal Cells to Osteosarcoma Cells Classification by Deep Learning

Mario D'Acunto, Massimo Martinelli, Davide Moroni

专题命中 病理影像 ：pathology(abstract)；diagnosis(abstract)；biomedical(abstract)；分类 cs.CV

Comments Submitted authors' version

Journal ref Journal of Intelligent & Fuzzy Systems, vol. 37, no. 6, pp. 7199-7206, 2019

Self supervised learning improves dMMR/MSI detection from histology slides across multiple cancers

Charlie Saillard, Olivier Dehaene, Tanguy Marchand, Olivier Moindrot, Aurélie Kamoun, Benoit Schmauch, Simon Jegou

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

Comments Accepted for poster and oral presentation at the MICCAI 2021 COMPAY Workshop (submitted the 19th of July 2021)

Journal ref Proceedings of the MICCAI Workshop on Computational Pathology, 156, 2021, 191-205

DenseNet for Breast Tumor Classification in Mammographic Images

Yuliana Jiménez Gaona, María José Rodriguez-Alvarez, Hector Espinó Morató, Darwin Castillo Malla, Vasudevan Lakshminarayanan

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

Comments to be submitted to The 2nd International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD2021)

Symb-xMIL: Symbolic Explanations for Multiple Instance Learning in Digital Pathology

Symb-xMIL: 数字病理学中多实例学习的符号解释

Yanqing Luo, Julius Hense, Niklas Prenißl, Andreas Mock, Klaus-Robert Müller, Thomas Schnake, Mina Jamshidi Idaji

机构 * Berlin Institute for the Foundations of Learning and Data（柏林学习与数据基础研究院） ； Machine Learning Group, Technische Universität Berlin（柏林技术大学机器学习组） ； Institute of Pathology, Charité Universitätsmedizin（查理研究所病理学部） ； Berlin Institute of Health at Charité – Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Digital Clinician Scientist Program（柏林查理医学研究院健康研究所、BIH生物医学创新学院、BIH查理数字临床科学家项目） ； Institute of Pathology, Ludwig Maximilian University of Munich（慕尼黑路德维希-马克西米利安大学病理学部） ； Division of Translational Medical Oncology, DKFZ（转化医学肿瘤学部，德国有机化学研究所） ； German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and Ludwig-Maximilians-Universität München (LMU)（德国癌症联盟（DKTK），慕尼黑合作伙伴站点，由DKFZ和路德维希-马克西米利安-慕尼黑大学（LMU）组成） ； Department of Artificial Intelligence, Korea University（韩国大学人工智能系） ； Max-Planck Institute for Informatics, Saarbrücken, Germany（马克斯·普朗克信息学院，萨尔布吕肯，德国） ； Department of Chemistry, Chemical Physics Theory Group, University of Toronto（多伦多大学化学系，化学物理理论组） ； Vector Institute for Artificial Intelligence, Toronto, Canada（多伦多人工智能矢量研究所） ； Acceleration Consortium, University of Toronto（多伦多大学加速联盟） 纠错

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

AI总结 提出Symb-xMIL框架，通过量化模型行为与可读决策规则（逻辑关系）的对齐程度，为多实例学习提供结构化的符号解释，并在合成和真实病理数据上验证其有效性。

Comments 23 pages, 18 figures

A Detection-Gated Pipeline for Robust Glottal Area Waveform Extraction and Clinical Pathology Assessment

一种用于鲁棒声门面积波形提取和临床病理评估的检测门控流程

Harikrishnan Unnikrishnan, Rita Patel

机构 * Orchard Robotics ； Department of Speech, Language, and Hearing Sciences（语音、语言和听力科学系） ； Indiana University（印第安纳大学） ； Department of Otolaryngology–Head and Neck Surgery（耳鼻喉科-头颈外科系） ； Indiana University School of Medicine（印第安纳大学医学院） 纠错

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

AI总结 本文提出一种两阶段模块化声门面积分割框架，用于高速视频喉镜，实现高精度、通用性和实时回放。结合YOLOv8n声门定位器和U-Net分割器，通过声门闭合时的门控机制减少伪分割。在GIRAFE和BAGLS数据集上训练，跨数据集评估显示其Dice相似系数达0.745，性能优于现有方法。

Comments for associated code see: https://github.com/hari-krishnan/openglottal

Hierarchical Generalized Category Discovery for Brain Tumor Classification in Digital Pathology

Matthias Perkonigg, Patrick Rockenschaub, Georg Göbel, Adelheid Wöhrer

机构 * Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics（临床流行病学、公共卫生、健康经济学、医学统计与信息学研究所） ； Institute of Neuropathology and Neuromolecular Pathology（神经病理学与神经分子病理学研究所） 纠错

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

Synergy vs. Noise: Performance-Guided Multimodal Fusion For Biochemical Recurrence-Free Survival in Prostate Cancer

Seth Alain Chang, Muhammad Mueez Amjad, Noorul Wahab, Ethar Alzaid, Nasir Rajpoot, Adam Shephard

机构 * Tissue Image Analytics Centre, Department of Computer Science, University of Warwick, UK（沃里克大学计算机科学系组织图像分析中心） 纠错

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

Comments 5 pages, 1 figure, 4 tables

SENCA-st: Integrating Spatial Transcriptomics and Histopathology with Cross Attention Shared Encoder for Region Identification in Cancer Pathology

Shanaka Liyanaarachchi, Chathurya Wijethunga, Shihab Aaqil Ahamed, Akthas Absar, Ranga Rodrigo

机构 * Dept. of Electronic and Telecommunication Engineering, University of Moratuwa（电子与电信工程系，穆塔瓦大学） 纠错

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

Comments Accepted at WACV 2026

Semantic Mosaicing of Histo-Pathology Image Fragments using Visual Foundation Models

Stefan Brandstätter, Maximilian Köller, Philipp Seeböck, Alissa Blessing, Felicitas Oberndorfer, Svitlana Pochepnia, Helmut Prosch, Georg Langs

机构 * Computational Imaging Research Lab（计算成像研究实验室） ； Division of General and Pediatric Radiology（普通放射科与小儿放射科 division） ； Christian Doppler Laboratory for Machine Learning Driven Precision Imaging（Christian Doppler 机器学习驱动的精准成像实验室） ； Comprehensive Center for Artificial Intelligence in Medicine（医学人工智能综合中心） ； Department of Pathology（病理学系） 纠错

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

SCC-YOLO: An Improved Object Detector for Assisting in Brain Tumor Diagnosis

Runci Bai, Guibao Xu, Yanze Shi

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

Open-source framework for detecting bias and overfitting for large pathology images

Anders Sildnes, Nikita Shvetsov, Masoud Tafavvoghi, Vi Ngoc-Nha Tran, Kajsa Møllersen, Lill-Tove Rasmussen Busund, Thomas K. Kilvær, Lars Ailo Bongo

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

Using Computer Vision for Skin Disease Diagnosis in Bangladesh Enhancing Interpretability and Transparency in Deep Learning Models for Skin Cancer Classification

Rafiul Islam, Jihad Khan Dipu, Mehedi Hasan Tusar

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

Comments 18 pages

Tissue Concepts: supervised foundation models in computational pathology

Till Nicke, Jan Raphael Schaefer, Henning Hoefener, Friedrich Feuerhake, Dorit Merhof, Fabian Kiessling, Johannes Lotz

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

Comments 22 Pages, 3 Figures, submitted to and under revision at Computers in Biology and Medicine

Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathology

Pedro Osorio, Guillermo Jimenez-Perez, Javier Montalt-Tordera, Jens Hooge, Guillem Duran-Ballester, Shivam Singh, Moritz Radbruch, Ute Bach, Sabrina Schroeder, Krystyna Siudak, Julia Vienenkoetter, Bettina Lawrenz, Sadegh Mohammadi

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

CVFC: Attention-Based Cross-View Feature Consistency for Weakly Supervised Semantic Segmentation of Pathology Images

Liangrui Pan, Lian Wang, Zhichao Feng, Liwen Xu, Shaoliang Peng

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

Comments Submitted to BIBM2023