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.

• Homepage: https://zenodo.org/record/53169#.XGZemKwzbmG
• Source code: tfds.image_classification.colorectal_histology.ColorectalHistology
• Versions:
  • 2.0.0 (default): New split API (tensorflow.org/datasets/splits)
• Download size: 246.14 MiB
• Dataset size: Unknown size
• Auto-cached (documentation): No
• Splits:

• 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),
})

• Supervised keys (See as_supervised doc): ('image', '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}
}