- Description:
10 large 5000 x 5000 textured colorectal cancer histology images
Homepage: https://zenodo.org/record/53169#.XGZemKwzbmG
Source code:
tfds.image_classification.ColorectalHistologyLargeVersions:
2.0.0(default): New split API (https://tensorflow.org/datasets/splits)
Download size:
707.65 MiBDataset size:
464.91 MiBAuto-cached (documentation): No
Splits:
| Split | Examples |
|---|---|
'test' |
10 |
- Feature structure:
FeaturesDict({
'filename': Text(shape=(), dtype=string),
'image': Image(shape=(5000, 5000, 3), dtype=uint8),
})
- Feature documentation:
| Feature | Class | Shape | Dtype | Description |
|---|---|---|---|---|
| FeaturesDict | ||||
| filename | Text | string | ||
| image | Image | (5000, 5000, 3) | uint8 |
Supervised keys (See
as_superviseddoc):NoneFigure (tfds.show_examples):
- Examples (tfds.as_dataframe):
- Citation:
@article{kather2016multi,
title={Multi-class texture analysis in colorectal cancer histology},
author={Kather, Jakob Nikolas and Weis, Cleo-Aron and Bianconi, Francesco and Melchers, Susanne M and Schad, Lothar R and Gaiser, Timo and Marx, Alexander and Z{"o}llner, Frank Gerrit},
journal={Scientific reports},
volume={6},
pages={27988},
year={2016},
publisher={Nature Publishing Group}
}