DOI: 10.5281/zenodo.15179607
title: HER2-IHC-40x: High-Resolution Histopathology Image Dataset for HER2 Scoring in Breast Cancer

description: HER2-IHC-40x: High-Resolution Histopathology Datasets for HER2 IHC Scoring

Please cite the dataset from the journal paper Click :

Nabi, M. S., Fauzi, M. F. A., Rehman, Z. U., Karim, H. B. A., Cheah, P. L., Chiew, S. F., & Looi, L. M. (2025). HER2-IHC-40x: A High-Resolution Histopathology Dataset for HER2 IHC Scoring in Breast Cancer. Data in Brief, 111922.

Here is the experimental paper; you may read and cite it as well for your own experiment.  Click:

Nabi, M. S., Fauzi, M. F. A., Karim, H. B. A., Cheah, P. L., Fan, C. S., & Looi, L. M. (2025). Explainable deep learning models for HER2 IHC scoring in breast cancer diagnosis. Informatics in Medicine Unlocked, 101700.

 

Overview

This dataset contains high-resolution histopathological images of HER2-stained breast cancer tissue sections. Designed for deep learning-based HER2 scoring, the dataset includes two variants:



HER2-IHC-40x: Patches extracted after splitting WSIs.

HER2-IHC-40x-WSI: Patches extracted before splitting.


Each image patch is categorized into one of four HER2 classes (0, 1+, 2+, 3+), based on staining intensity.

 

Dataset Contents

Dataset Variants

1. HER2-IHC-40x



WSI-based 80-20 split before patch extraction.

107 WSIs → 9940 patches (8093 train / 1847 test)


2. HER2-IHC-40x-WSI



Patch-based 80-20 split after patch extraction.

107 WSIs → 10,997 patches (8897 train / 2200 test)


 

Folder Structure

HER2-IHC-40x/

├── WSI/              # Original Whole Slide Images (.svs)

├── ROI/              # Expert-annotated tumor regions (.png)

├── Patches/       # 1024x1024 image patches, labeled 0, 1+, 2+, 3+

├── Train/           # 80% training set

└── Test/            # 20% test set

 

HER2-IHC-40x-WSI/

├── Patches/

├── Train/

└── Test/

 

 

HER2 Class Definitions

 

| HER2 Score | Description                                                                 

|----------|-----------------------------------------------------------------------------

| 0           | No observable staining                                                                      

| 1+         | Weak/incomplete membrane staining in ≤10% tumor cells                       

| 2+         | Moderate circumferential staining in >10% tumor cells (Equivocal)           

| 3+         | Strong circumferential staining in >10% tumor cells (Positive)              

 

Preprocessing & Quality Control



ROI Selection: Manual annotation by expert pathologists using Cytomine.

Color Histogram Filtering: Removed non-tumor/low-quality patches using HSV filtering.

Normalization: Intensity normalization across all patches.

Patch Extraction: Adaptive 1024×1024 extraction using sliding window method.


 

Usage

This dataset is suitable for:



HER2 scoring automation using deep learning

Explainable AI (Grad-CAM, attention models)

Color normalization and domain adaptation

Model benchmarking and generalization research


 

Dataset Statistics

 

HER2-IHC-40x (WSI Split)

| HER2 Class | WSIs | ROIs | Patches |

|----------|------|----- -|---------|

| 0            | 23   | 429   | 3789    |

| 1+         | 26   | 131   | 2153    |

| 2+         | 27   | 483   | 634     |

| 3+         | 31   | 156   | 3364    |

| Total      | 107 | 1199 | 9940    |

 

HER2-IHC-40x (Patch Split)

| HER2 Class | WSIs | ROIs | Patches |

|----------|-----|--------|---------|

| 0           | 23   | 429     | 3789    |

| 1+         | 26   | 131    | 2689    |

| 2+         | 27   | 483    | 1131    |

| 3+         | 31   | 156    | 3388    |

| Total      | 107  | 1199 | 10,997  |

 



Citation

The dataset is already published as a journal article: If you use this dataset, please cite:



@article{nabi2025her2,
  title={HER2-IHC-40x: A High-Resolution Histopathology Dataset for HER2 IHC Scoring in Breast Cancer},
  author={Nabi, Md Serajun and Fauzi, Mohammad Faizal Ahmad and Rehman, Zaka Ur and Karim, Hezerul Bin Abdul and Cheah, Phaik Leng and Chiew, Seow Fan and Looi, Lai Meng},
  journal={Data in Brief},
  pages={111922},
  year={2025},
  publisher={Elsevier}
}


 

APA



Nabi, M. S., Fauzi, M. F. A., Rehman, Z. U., Karim, H. B. A., Cheah, P. L., Chiew, S. F., & Looi, L. M. (2025). HER2-IHC-40x: A High-Resolution Histopathology Dataset for HER2 IHC Scoring in Breast Cancer. Data in Brief, 111922.


 

 

This dataset is part of the research article:

**"Enhancing HER2 IHC Scoring Using HRNet and SwinT with Cross-Dataset Generalization"**  

Authors: Md Serajun Nabi, Mohammad Faizal Ahmad Fauzi, Hezerul Bin Abdul Karim, et al.  

(Preprint server or journal details to be confirmed.)

 

Search the paper for detail data description:

**HER2-IHC-40x: High-Resolution Histopathology Datasets for HER2 IHC Scoring**

The color histogram code source:* https://github.com/seraju77/HER2-IHC-40x-data-preprocessing.git *