Histopathology Image Classification

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Overview

Histopathology image classification studies how to recognize disease and clinically relevant tissue patterns in microscope images, from small patches and cells to whole-slide images (WSIs). Common approaches include convolutional and vision-transformer models, pathology foundation models, and multiple-instance learning (MIL), which uses slide-level labels to combine evidence from many patches; newer methods also model spatial structure, multiple magnifications, and clinical or molecular data. These systems are evaluated on tasks such as tumor detection, cancer subtyping, grading, and biomarker prediction, using public benchmarks and increasingly external, multicenter, or prospective clinical settings. A central challenge is maintaining reliable performance across sites, stains, scanners, and patient groups while ensuring models use meaningful diagnostic evidence and provide calibrated, interpretable predictions at feasible computational cost.

Latest papers

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146 papers18 papers in the last four weeks, up 20% on the four weeks before. 0.1% of all new papers.

  1. Leveraging Cell-level Spatial Transcriptomics as Weak Supervision for Nuclei Classification

    Apr 26, 2026Kazuya Nishimura, Ryoma Bise, Haruka Hirose +1Computational PathologyHistopathology Image Segmentation

    The University of Osaka, Osaka, Japan · National Cancer Center Tokyo, Japan · Kyushu University, Fukuoka, Japan

  2. Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Images

    Apr 22, 2026Joakim Nguyen, Jian Yu, Jinrui Fang +7Pathology Foundation ModelsMedical Image Classification

    Dept. of Computer Science University of Texas at Austin Austin, TX, USA · School of Information University of Texas at Austin Austin, TX, USA · Dept. of Computer Science UNC at Chapel Hill Chapel Hill, NC, USA +3

  3. A Digital Pathology Resource for Liver Cancer Quantification with Datasets, Benchmarks, and Tools

    Apr 22, 2026Ying Xiao, Shimiao Tang, Xitong Ling +11Computational PathologyImage Segmentation

    Department of Pathology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China · Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

  4. Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localization

    Apr 21, 2026Tianyang Wang, Ziyu Su, Abdul Rehman Akbar +6Pathology Foundation ModelsOncology

    Department of Pathology, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA · Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA

  5. Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging

    Apr 19, 2026Nagur Shareef Shaik, Teja Krishna Cherukuri, Dong Hye YeMedical Image ClassificationHistopathology Image Classification

    Department of Computer Science, Georgia State University, Atlanta, GA USA

  6. Multimodal Fusion of Histopathology Images and Electronic Health Records for Early Breast Cancer Diagnosis

    Apr 18, 2026Aditya Shribhagwan Khandelwal, Mohammad Samar Ansari, Asra AslamBreast CancerComputational Pathology

    University of Sheffield, UK · University of Chester, UK

  7. Dual-Modal Lung Cancer AI: Interpretable Radiology and Microscopy with Clinical Risk Integration

    Apr 17, 2026Baramee Sukumal, Aueaphum AueawatthanaphisutMedical Image ClassificationExplainable Medical Image Analysis

    Hatyaiwittayalai School, Hat Yai, Songkhla, Thailand, 90110 · School of Information, Computer, and Communication Technology,2026 Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, Thailand

  8. SSMamba: A Self-Supervised Hybrid State Space Model for Pathological Image Classification

    Apr 17, 2026Enhui Chai, Sicheng Chen, Tianyi Zhang +2Self-Supervised LearningPathology Foundation Models

    School of Computer Science, Northwest University · PuzzleLogic Pte Ltd, Singapore 229594, Singapore · Department of Electrical & Computer Engineering, National University of Singapore +1

  9. Artificial intelligence application in lymphoma diagnosis with Vision Transformer using weakly supervised training

    Apr 15, 2026Nghia, Nguyen, Amer Wahed +9Histopathology Image ClassificationOncology

    Andy · Department of Pathology and Laboratory Medicine, The University of Texas McGovern Medical School, Houston, Texas · Department of Hematopathology, The University of Texas MD Anderson Cancer, Houston, Texas

  10. PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning

    Apr 13, 2026Syed Fahim Ahmed, Gnanesh Rasineni, Florian Koehler +7Whole-Slide Image AnalysisHistopathology Image Classification

    Kahlert School of Computing, University of Utah, Salt Lake City, UT 84112, USA · Scientific Computing & Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA · Instapath Inc., Houston, TX 77021, USA +1

  11. DSVTLA: Deep Swin Vision Transformer-Based Transfer Learning Architecture for Multi-Type Cancer Histopathological Cancer Image Classification

    Apr 10, 2026Muazzem Hussain Khan, Tasdid Hasnain, Md. Jamil khan +4Histopathology Image ClassificationHybrid CNN-Transformer Architectures

    Department of Computer Science and Engineering, Metropolitan University, Sylhet-3104 · Department of Statistics, Pabna University of Science and Technology, Pabna-6600, Bangladesh · Department of Computer Science and Engineering, Rajshahi University of Engineering and Technology, Rajshahi-6204, Bangladesh +1

  12. Shortcut Learning in Glomerular AI: Adversarial Penalties Hurt, Entropy Helps

    Apr 9, 2026Mohammad Daouk, Jan Ulrich Becker, Neeraja Kambham +3Shortcut LearningHistopathology Image Classification

    University of Houston, Houston, TX, USA · University Hospital Cologne, Cologne, Germany · Stanford University, Stanford, CA, USA +1

  13. Plug-and-Play Logit Fusion for Heterogeneous Pathology Foundation Models

    Apr 9, 2026Gexin Huang, Anqi Li, Yusheng Tan +4Computational PathologyEnsemble Learning

    University of British Columbia, Vancouver, BC, Canada · Vector Institute, Toronto, ON, Canada · Washington University in St. Louis, St. Louis, MO, USA

  14. Region-Graph Optimal Transport Routing for Mixture-of-Experts Whole-Slide Image Classification

    Apr 8, 2026Xin Tian, Jiuliu Lu, Ephraim Tsalik +3Histopathology Image ClassificationWhole-Slide Image Analysis

    Centre for Human Genetics, University of Oxford, Oxford, UK · Beckman Coulter Diagnostics, Brea, CA, USA · Danaher Corporation, Washington, DC, USA

  15. MedGemma 1.5 Technical Report

    Apr 6, 2026Andrew Sellergren, Chufan Gao, Fereshteh Mahvar +39Medical Imaging Foundation Models3D Medical Imaging

  16. A deep learning pipeline for PAM50 subtype classification using histopathology images and multi-objective patch selection

    Apr 2, 2026Arezoo Borji, Gernot Kronreif, Bernhard Angermayr +6Monte Carlo DropoutHistopathology Image Classification

    Austrian Center for Medical Innovation and Technology, Wiener Neustadt, Austria · Department of Medicine, Faculty of Medicine and Dentistry, Danube Private University, Krems an der Donau, Austria. · Department of Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria +3

  17. Dictionary-based Pathology Mining with Hard-instance-assisted Classifier Debiasing for Genetic Biomarker Prediction from WSIs

    Mar 26, 2026Ling Zhang, Boxiang Yun, Ting Jin +3Computational PathologyHistopathology Image Classification

    Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai, China · Department of General Surgery, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China

  18. Mixture of Mini Experts: Overcoming the Linear Layer Bottleneck in Multiple Instance Learning

    Mar 23, 2026Daniel Shao, Joel Runevic, Richard J. Chen +4Multiple Instance LearningHistopathology Image Classification

    Massachusetts Institute of Technology, Cambridge MA · Harvard University, Cambridge MA · Emory University, Atlanta GA +1

  19. Jigsaw Regularization in Whole-Slide Image Classification

    Mar 20, 2026So Won Jeong, Veronika RočkováHistopathology Image ClassificationWhole-Slide Image Analysis

    Booth School of Business, The University of Chicago, IL, USA.

  20. ReconMIL: Synergizing Latent Space Reconstruction with Bi-Stream Mamba for Whole Slide Image Analysis

    Mar 20, 2026Lubin Gan, Jing Zhang, Heng Zhang +4Histopathology Image ClassificationMedical Image Localization

    USTC, Anhui, China · Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing, Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Anhui, China · SCNU, Guangdong, China +2

  21. Domain Adaptation Without the Compute Burden for Efficient Whole Slide Image Analysis

    Mar 16, 2026Umar Marikkar, Muhammad Awais, Sara AtitoWhole-Slide Image AnalysisComputational Pathology

    Institute for People-Centered AI, University of Surrey · Centre of Vision, Speech and Signal Processing, University of Surrey

  22. Histo-MExNet: A Unified Framework for Real-World, Cross-Magnification, and Trustworthy Breast Cancer Histopathology

    Mar 15, 2026Enam Ahmed Taufika, Md Ahasanul Arafatha, Abhijit Kumar Ghoshb +2Histopathology Image ClassificationExplainable Medical Image Analysis

    European University of Bangladesh, Department of Computer Science and Engineering, Dhaka, Bangladesh · BRAC University, Department of Computer Science and Engineering, Dhaka, Bangladesh · Ochsner Center for Outcomes Research, Ochsner Research, Ochsner Clinic Foundation, New Orleans, LA, 70121, USA

  23. Every Error has Its Magnitude: Asymmetric Mistake Severity Training for Multiclass Multiple Instance Learning

    Mar 14, 2026Sungrae Hong, Jiwon Jeong, Jisu Shin +4Multiple Instance LearningCost-Sensitive Learning

    Korea Advanced Institute of Science and Technology, Daejeon, South Korea · Seegene Medical Foundation, Seoul, South Korea

  24. A protocol for evaluating robustness to H&E staining variation in computational pathology models

    Mar 13, 2026Lydia A. Schönpflug, Nikki van den Berg, Sonali Andani +5Computational PathologyMicroscopy Image Analysis

  25. Selective Prediction Forgetting for Adaptation of Weakly Supervised Localization of Histology Images

    Mar 12, 2026Alexis Guichemerre, Banafsheh Karimian, Soufiane Belharbi +6Source-Free Domain AdaptationWeakly Supervised Learning

    ÉTS Montréal, Montreal, Canada · Sorbonne Université, Paris, France · University of York, York, United Kingdom +1

  26. Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Images

    Mar 12, 2026Michael Okonoda, Eder Martinez, Abhilekha Dalal +1Dataset BiasConvolutional Neural Networks

    Department of Computer Science, Kansas State University, Manhattan, KS 66506, USA

  27. Automated Detection of Malignant Lesions in the Ovary Using Deep Learning Models and XAI

    Mar 12, 2026Md. Hasin Sarwar Ifty, Nisharga Nirjan, Labib Islam +4Histopathology Image ClassificationComputational Pathology

    Dept. of Computer Science and Engr. BRAC University Dhaka, Bangladesh

  28. DeepHistoViT: An Interpretable Vision Transformer Framework for Histopathological Cancer Classification

    Mar 12, 2026Ravi Mosalpuri, Mohammed Abdelsamea, Ahmed Karam EldalyHistopathology Image ClassificationComputational Pathology

  29. Leveraging whole slide difficulty in Multiple Instance Learning to improve prostate cancer grading

    Mar 10, 2026Marie Arrivat, Rémy Peyret, Elsa Angelini +1Prostate Cancer GradingHistopathology Image Classification

    Primaa, Paris, France · LTCI, Telecom Paris, Institut Polytechnique de Paris, France

  30. Class Visualizations and Activation Atlases for Enhancing Interpretability in Deep Learning-Based Computational Pathology

    Mar 7, 2026Marco Gustav, Fabian Wolf, Christina Glasner +6Feature VisualizationExplainable Medical Image Analysis

    Else Kroener Fresenius Center for Digital Health, Faculty of Medicine, TUD Dresden University of Technology, Dresden, Germany · Institute of Pathology, University Medical Center Mainz, Mainz, Germany · Pathology, Faculty of Medicine, University of Augsburg, Augsburg, Germany +4