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classification-of-HnE-stained-histological-breast-cancer-images/README.md

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+## Details
+The image dataset is composed of high-resolution (2040 × 1536 pixels), uncompressed, and annotated H&E stain images from the Bioimaging 2015 breast histology classification challenge [3]. All the images are digitized with the same acquisition conditions, with magnification of 200× and pixel size of 0.42μm × 0.42μm. Each image is labeled with one of four classes: i) normal tissue, ii) benign lesion, iii) in situ carcinoma and iv) invasive carcinoma
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+Input size = 512 x 512 x 3
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 ## Citation
 In this notebook, there's a Keras implementation of the patch-wise network of the paper <a href="https://arxiv.org/abs/1803.04054">Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification</a>:
 
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   year={2018},
   organization={Springer}
 }
-```
+```