colorectal_histology

  • Description:

Classification of textures in colorectal cancer histology. Each example is a 150 x 150 x 3 RGB image of one of 8 classes.

Split Examples
'train' 5,000
  • Feature structure:
FeaturesDict({
    'filename': Text(shape=(), dtype=string),
    'image': Image(shape=(150, 150, 3), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=8),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
filename Text string
image Image (150, 150, 3) uint8
label ClassLabel int64 Eight classes: 0: 'tumour epithelium', 1: 'simple stroma', 2: 'complex stroma' (stroma that contains single tumour cells and/or single immune cells), 3: 'immune cell conglomerates', 4: 'debris and mucus', 5: 'mucosal glands', 6: 'adipose tissue', and 7: 'background'.

Visualization

  • 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}
}