ArticleData in brief2025
HER2-IHC-40x: A high-resolution histopathology dataset for HER2 IHC scoring in breast cancer.
Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- AI-Driven Breast Cancer Nuclei Segmentation, Classification, and Scoring in PR-IHC Images.Diagnostics (Basel, Switzerland) · 2026Article
- Companion Diagnostics in Clinical Therapy: Current Applications and Future Directions.MedComm · 2026Review
- Bridging Global Attention and Local Hierarchies: A Robust Hybrid Ensemble Framework With Multi-Perspective Explainability for Automated HER2-IHC Scoring.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The HER2-IHC-40x and HER2-IHC-40x-WSI datasets are high-resolution whole slide image (WSI) and patch-extracted region collection for HER2 immunohistochemistry (IHC) scoring in breast cancer pathology. 107 WSIs are scanned at 40 × magnification with Regions of Interest (ROIs) annotated by expert pathologists. Patches of 1024 × 1024 pixels are extracted from the ROIs and classified into four HER2 scores (0, 1+, 2+, 3+), yielding structured data for computational pathology analysis. There were two strategies of splitting: WSI-based split, where data was first split before extracting the patches and named as HER2-IHC-40x for this dataset, the other one is patch-based split, where patches were extracted first and then split, named as HER2-IHC-40x-WSI of this dataset. The filtering method for color histograms was applied to remove the non-tumour regions and artifacts, generating high-quality data. The dataset is applicable to deep learning applications, including HER2 classification and explainable AI. It is freely available on Zenodo, with preprocessing scripts provided via GitHub, enabling reproducibility in digital pathology research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.