Update README.md

README.md

@@ -1,3 +1,45 @@
 ---
 license: cc-by-nc-nd-4.0
+size_categories:
+- 1K<n<10K
+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