colorectal_histology

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

• URL: https://zenodo.org/record/53169#.XGZemKwzbmG
• DatasetBuilder: tfds.image.colorectal_histology.ColorectalHistology
• Version: v0.0.1

• Versions:

  • 0.0.1 (default):
  • 2.0.0: New split API (https://tensorflow.org/datasets/splits)

• Size: 246.14 MiB

Features

FeaturesDict({
    'filename': Text(shape=(), dtype=tf.string),
    'image': Image(shape=(150, 150, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=8),
})

Statistics

Homepage

• https://zenodo.org/record/53169#.XGZemKwzbmG

Supervised keys (for as_supervised=True)

(u'image', u'label')

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}
}