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
Split | Examples |
---|---|
ALL | 5,000 |
TRAIN | 5,000 |
Homepage
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}
}