README.md

---
license: cc-by-nc-nd-4.0
size_categories:
- n<1K
task_categories:
- image-classification
tags:
- biology
- Histopathology
- Histology
- Digital Pathology
- Breast Cancer
---

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3632035.svg)](https://doi.org/10.5281/zenodo.3632035)

# BACH Dataset : Grand Challenge on Breast Cancer Histology images

**Homepage**: https://zenodo.org/records/3632035 \
**Homepage**: https://iciar2018-challenge.grand-challenge.org/ \
**Publication Date**: 2019-05-31 \
**License**: [Creative Commons Attribution Non Commercial No Derivatives 4.0 International](https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode) \
**Citation**:
```bibtex
@dataset{polonia_2020_3632035,
  author    = {Polónia, António and Eloy, Catarina and Aguiar, Paulo},
  title     = {{BACH Dataset : Grand Challenge on Breast Cancer Histology images}},
  month     = jan,
  year      = 2020,
  publisher = {Zenodo}
}
```

## Description

The dataset is composed of Hematoxylin and eosin (H&E) stained breast histology microscopy images.

Microscopy images are labelled as normal, benign, in situ carcinoma or invasive carcinoma according to the predominant cancer type in each image.
The annotation was performed by two medical experts and images where there was disagreement were discarded.
Images have the following specifications:
  * Color model: R(ed)G(reen)B(lue)
  * Size: 2048 x 1536 pixels
  * Pixel scale: 0.42 µm x 0.42 µm
  * Memory space: 10-20 MB (approx.)
  * Type of label: image-wise