mlsanityData to 7 Oct 2026

On Image Search in Histopathology

arXiv 2401.08699 ↗First posted 14 Jan 2024eess.IV cs.AI cs.CVcited by 12

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Abstract (arXiv)

Pathology images of histopathology can be acquired from camera-mounted microscopes or whole slide scanners. Utilizing similarity calculations to match patients based on these images holds significant potential in research and clinical contexts. Recent advancements in search technologies allow for implicit quantification of tissue morphology across diverse primary sites, facilitating comparisons and enabling inferences about diagnosis, and potentially prognosis, and predictions for new patients when compared against a curated database of diagnosed and treated cases. In this paper, we comprehensively review the latest developments in image search technologies for histopathology, offering a concise overview tailored for computational pathology researchers seeking effective, fast and efficient image search methods in their work.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 12 of its 70 references that are in the map. First posted on arXiv 14 Jan 2024.

Builds on

12 of 70 references.

References · 12

  1. 2023HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attributioncited by 55
  2. 2019Similar Image Search for Histopathology: SMILYcited by 41
  3. 2017Medical Image Retrieval using Deep Convolutional Neural Networkcited by 33
  4. 2019Pan-Cancer Diagnostic Consensus Through Searching Archival Histopathology Images Using Artificial Intelligencecited by 26
  5. 2022Learning to Predict RNA Sequence Expressions from Whole Slide Images with Applications for Search and Classificationcited by 14
  6. 2018Deep Barcodes for Fast Retrieval of Histopathology Scanscited by 9
  7. 2017On the Behavior of Convolutional Nets for Feature Extractioncited by 8
  8. 2023When is a Foundation Model a Foundation Modelcited by 7
  9. 2022Hospital-Agnostic Image Representation Learning in Digital Pathologycited by 6
  10. 2015Barcode Annotations for Medical Image Retrieval: A Preliminary Investigationcited by 5
  11. 2022LILE: Look In-Depth before Looking Elsewhere -- A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archivescited by 5
  12. 2023Comments on 'Fast and scalable search of whole-slide images via self-supervised deep learning'cited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 5; 2025: 4; 2026: 3.

12 papers.

  1. 2025PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Imagescited by 9
  2. 2024SPLICE -- Streamlining Digital Pathology Image Processingcited by 4
  3. 2024On Validation of Search & Retrieval of Tissue Images in Digital Pathologycited by 1
  4. 2024A Short Survey on Set-Based Aggregation Techniques for Single-Vector WSI Representation in Digital Pathologycited by 1
  5. 2024Multimodal Learning for Scalable Representation of High-Dimensional Medical Datacited by 1
  6. 2024Advancing Histopathology-Based Breast Cancer Diagnosis: Insights into Multi-Modality and Explainabilitycited by 0
  7. 2025Aggregation Schemes for Single-Vector WSI Representation Learning in Digital Pathologycited by 0
  8. 2025THIR: Topological Histopathological Image Retrievalcited by 0
  9. 2025mViSE: A Visual Search Engine for Analyzing Multiplex IHC Brain Tissue Imagescited by 0
  10. 2026Validation of Whole-Slide Foundation Models for Image Retrieval in TCGA Datacited by 0
  11. 2026CRISP -- Clustering-Based Redundancy-Reduced Instance Sampling for Pathology Case Representation and Retrievalcited by 0
  12. 2026Reducing Redundancy in Whole-Slide Image Patching for Scalable Indexing and Retrievalcited by 0