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Machine learning methods for histopathological image analysis

arXiv 1709.00786 ↗First posted 4 Sep 2017cs.CVcited by 79

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Abstract (arXiv)

Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have some issues to be considered. In this mini-review, we introduce the application of digital pathological image analysis using machine learning algorithms, address some problems specific to such analysis, and propose possible solutions.

Key facts. Cited by 79 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Sep 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 18; 2022: 18; 2023: 14; 2024: 11; 2025: 12; 2026: 6.

79 papers.

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  1. 2021Extending the WILDS Benchmark for Unsupervised Adaptationcited by 85
  2. 2021Hierarchical Graph Representations in Digital Pathologycited by 58
  3. 2021CryoNuSeg: A Dataset for Nuclei Instance Segmentation of Cryosectioned H&E-Stained Histological Imagescited by 50
  4. 2021A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approachescited by 44
  5. 2022Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalizationcited by 34
  6. 2021Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentationcited by 26
  7. 2023SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathologycited by 26
  8. 2022FHIST: A Benchmark for Few-shot Classification of Histological Imagescited by 20
  9. 2021Self-learning for weakly supervised Gleason grading of local patternscited by 14
  10. 2024The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Imagescited by 13
  11. 2022Multi stain graph fusion for multimodal integration in pathologycited by 11
  12. 2021Machine Learning Methods for Histopathological Image Analysis: A Reviewcited by 10
38 more
  1. 2021WeGleNet: A Weakly-Supervised Convolutional Neural Network for the Semantic Segmentation of Gleason Grades in Prostate Histology Imagescited by 9
  2. 2021Self-Rule to Multi-Adapt: Generalized Multi-source Feature Learning Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Detectioncited by 9
  3. 2022Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Imagescited by 9
  4. 2022From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in Histopathologycited by 9
  5. 2024Source-Free Domain Adaptation of Weakly-Supervised Object Localization Models for Histologycited by 9
  6. 2025HistoViT: Vision Transformer for Accurate and Scalable Histopathological Cancer Diagnosiscited by 9
  7. 2022Negative Evidence Matters in Interpretable Histology Image Classificationcited by 8
  8. 2024Boosting Vision-Language Models for Histopathology Classification: Predict all at oncecited by 8
  9. 2021Prediction of lung and colon cancer through analysis of histopathological images by utilizing Pre-trained CNN models with visualization of class activation and saliency mapscited by 7
  10. 2021A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformerscited by 7
  11. 2021Multi-scale Deep Learning Architecture for Nucleus Detection in Renal Cell Carcinoma Microscopy Imagecited by 7
  12. 2022Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutationcited by 7
  13. 2023Imbalanced Domain Generalization for Robust Single Cell Classification in Hematological Cytomorphologycited by 7
  14. 2023Reconstruction, forecasting, and stability of chaotic dynamics from partial datacited by 7
  15. 2023Generalizing to Unseen Domains in Diabetic Retinopathy Classificationcited by 7
  16. 2024MergeUp-augmented Semi-Weakly Supervised Learning for WSI Classificationcited by 7
  17. 2025Generative Classifiers Avoid Shortcut Solutionscited by 7
  18. 2022Rethinking Machine Learning Model Evaluation in Pathologycited by 5
  19. 2022Data Models for Dataset Drift Controls in Machine Learning With Optical Imagescited by 5
  20. 2023Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithmscited by 5
  21. 2022Gated Domain Units for Multi-source Domain Generalizationcited by 4
  22. 2024SPLICE -- Streamlining Digital Pathology Image Processingcited by 4
  23. 2024Path-SAM2: Transfer SAM2 for digital pathology semantic segmentationcited by 4
  24. 2023AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Imagecited by 3
  25. 2023Ranking Loss and Sequestering Learning for Reducing Image Search Bias in Histopathologycited by 3
  26. 2023GenSelfDiff-HIS: Generative Self-Supervision Using Diffusion for Histopathological Image Segmentationcited by 3
  27. 2025Semantic and Visual Crop-Guided Diffusion Models for Heterogeneous Tissue Synthesis in Histopathologycited by 3
  28. 2023Active Learning Based Domain Adaptation for Tissue Segmentation of Histopathological Imagescited by 2
  29. 2024MEATRD: Multimodal Anomalous Tissue Region Detection Enhanced with Spatial Transcriptomicscited by 2
  30. 2021Synthetic Generation of Three-Dimensional Cancer Cell Models from Histopathological Imagescited by 1
  31. 2021Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasmscited by 1
  32. 2022Neuroplastic graph attention networks for nuclei segmentation in histopathology imagescited by 1
  33. 2022Clustering and classification of low-dimensional data in explicit feature map domain: intraoperative pixel-wise diagnosis of adenocarcinoma of a colon in a livercited by 1
  34. 2022MGTUNet: An new UNet for colon nuclei instance segmentation and quantificationcited by 1
  35. 2022Deep Neural Networks integrating genomics and histopathological images for predicting stages and survival time-to-event in colon cancercited by 1
  36. 2024Beyond accuracy: quantifying the reliability of Multiple Instance Learning for Whole Slide Image classificationcited by 1
  37. 2025Latent Gene Diffusion for Spatial Transcriptomics Completioncited by 1
  38. 2025MambaMIL+: Modeling Long-Term Contextual Patterns for Gigapixel Whole Slide Imagecited by 1

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