mlsanityData to 7 Oct 2026

Rotation-Agnostic Image Representation Learning for Digital Pathology

arXiv 2311.08359 ↗First posted 14 Nov 2023cs.CVcited by 15

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Abstract (arXiv)

This paper addresses complex challenges in histopathological image analysis through three key contributions. Firstly, it introduces a fast patch selection method, FPS, for whole-slide image (WSI) analysis, significantly reducing computational cost while maintaining accuracy. Secondly, it presents PathDino, a lightweight histopathology feature extractor with a minimal configuration of five Transformer blocks and only 9 million parameters, markedly fewer than alternatives. Thirdly, it introduces a rotation-agnostic representation learning paradigm using self-supervised learning, effectively mitigating overfitting. We also show that our compact model outperforms existing state-of-the-art histopathology-specific vision transformers on 12 diverse datasets, including both internal datasets spanning four sites (breast, liver, skin, and colorectal) and seven public datasets (PANDA, CAMELYON16, BRACS, DigestPath, Kather, PanNuke, and WSSS4LUAD). Notably, even with a training dataset of 6 million histopathology patches from The Cancer Genome Atlas (TCGA), our approach demonstrates an average 8.5% improvement in patch-level majority vote performance. These contributions provide a robust framework for enhancing image analysis in digital pathology, rigorously validated through extensive evaluation. Project Page: https://kimialabmayo.github.io/PathDino-Page/

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 39 of its 57 references that are in the map. First posted on arXiv 14 Nov 2023.

Builds on

39 of 57 references.

References · 39

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  5. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
  6. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
  7. 2016Densely Connected Convolutional Networkscited by 6,691
  8. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  9. 2022A ConvNet for the 2020scited by 3,545
  10. 2020Unsupervised Learning of Visual Features by Contrasting Cluster Assignmentscited by 2,845
  11. 2020Improved Baselines with Momentum Contrastive Learningcited by 2,282
  12. 2021Barlow Twins: Self-Supervised Learning via Redundancy Reductioncited by 1,818
27 more
  1. 2021iBOT: Image BERT Pre-Training with Online Tokenizercited by 891
  2. 2020Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Imagescited by 738
  3. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 549
  4. 2020Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learningcited by 473
  5. 2022Scaling Vision Transformers to Gigapixel Images via Hierarchical Self-Supervised Learningcited by 357
  6. 2021Big Self-Supervised Models Advance Medical Image Classificationcited by 320
  7. 2022DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image Classificationcited by 254
  8. 2020Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Learning Networkscited by 178
  9. 2022Benchmarking Self-Supervised Learning on Diverse Pathology Datasetscited by 148
  10. 2020Self supervised contrastive learning for digital histopathologycited by 146
  11. 2021BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Imagescited by 130
  12. 2020PanNuke Dataset Extension, Insights and Baselinescited by 113
  13. 2023Interventional Bag Multi-Instance Learning On Whole-Slide Pathological Imagescited by 91
  14. 2023Virchow: A Million-Slide Digital Pathology Foundation Modelcited by 86
  15. 2022What Makes Transfer Learning Work For Medical Images: Feature Reuse & Other Factorscited by 61
  16. 2023Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image Classificationcited by 54
  17. 2021Fine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slidescited by 52
  18. 2023Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learningcited by 47
  19. 2021A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approachescited by 44
  20. 2019Yottixel -- An Image Search Engine for Large Archives of Histopathology Whole Slide Imagescited by 41
  21. 2022WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinomacited by 32
  22. 2023Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image Classificationcited by 27
  23. 2021Self-Supervised Representation Learning using Visual Field Expansion on Digital Pathologycited by 25
  24. 2019Self-Supervised Similarity Learning for Digital Pathologycited by 22
  25. 2020Multi-task pre-training of deep neural networks for digital pathologycited by 14
  26. 2022ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Imagescited by 11
  27. 2022A review of machine learning approaches, challenges and prospects for computational tumor pathologycited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 6; 2026: 5.

15 papers.

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  1. 2024F2FLDM: Latent Diffusion Models with Histopathology Pre-Trained Embeddings for Unpaired Frozen Section to FFPE Translationcited by 6
  2. 2025Beyond the Failures: Rethinking Foundation Models in Pathologycited by 6
  3. 2024Diagnostic Text-guided Representation Learning in Hierarchical Classification for Pathological Whole Slide Imagecited by 4
  4. 2025Semantic and Visual Crop-Guided Diffusion Models for Heterogeneous Tissue Synthesis in Histopathologycited by 3
  5. 2024SRA: A Novel Method to Improve Feature Embedding in Self-supervised Learning for Histopathological Imagescited by 2
  6. 2025WeakSupCon: Weakly Supervised Contrastive Learning for Encoder Pre-trainingcited by 2
  7. 2025A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Featurescited by 2
  8. 2024Efficient Self-Supervised Barlow Twins from Limited Tissue Slide Cohorts for Colonic Pathology Diagnosticscited by 1
  9. 2025Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Imagescited by 0
  10. 2025Overfitting in Histopathology Model Training: The Need for Customized Architecturescited by 0
  11. 2026Weakly Supervised Contrastive Learning for Histopathology Patch Embeddingscited by 0
  12. 2026Benchmarking Computational Pathology Foundation Models For Semantic Segmentationcited by 0
3 more
  1. 2026Efficient AI-Driven Multi-Section Whole Slide Image Analysis for Biochemical Recurrence Prediction in Prostate Cancercited by 0
  2. 2026LEMON: a foundation model for nuclear morphology in Computational Pathologycited by 0
  3. 2026Retrieval-Guided Generation for Safer Histopathology Image Captioningcited by 0