The dataset viewer is not available for this split.
The info cannot be fetched for the config 'default' of the dataset.
Error code:   InfoError
Exception:    HfHubHTTPError
Message:      429 Client Error: Too Many Requests for url: https://huggingface.co/api/datasets/1aurent/Kather-texture-2016
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 218, in compute_first_rows_from_streaming_response
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 478, in get_dataset_config_info
                  builder = load_dataset_builder(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 2259, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1910, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1855, in dataset_module_factory
                  raise e
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1828, in dataset_module_factory
                  dataset_info = hf_api.dataset_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2347, in dataset_info
                  hf_raise_for_status(r)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_errors.py", line 371, in hf_raise_for_status
                  raise HfHubHTTPError(str(e), response=response) from e
              huggingface_hub.utils._errors.HfHubHTTPError: 429 Client Error: Too Many Requests for url: https://huggingface.co/api/datasets/1aurent/Kather-texture-2016

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Collection of textures in colorectal cancer histology

Description

This data set represents a collection of textures in histological images of human colorectal cancer. It contains 5000 histological images of 150 * 150 px each (74 * 74 µm). Each image belongs to exactly one of eight tissue categories.

Image format

All images are RGB, 0.495 µm per pixel, digitized with an Aperio ScanScope (Aperio/Leica biosystems), magnification 20x. Histological samples are fully anonymized images of formalin-fixed paraffin-embedded human colorectal adenocarcinomas (primary tumors) from our pathology archive (Institute of Pathology, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany).

Ethics statement

All experiments were approved by the institutional ethics board (medical ethics board II, University Medical Center Mannheim, Heidelberg University, Germany; approval 2015-868R-MA). The institutional ethics board waived the need for informed consent for this retrospective analysis of anonymized samples. All experiments were carried out in accordance with the approved guidelines and with the Declaration of Helsinki.

More information / data usage

For more information, please refer to the following article. Please cite this article when using the data set.
Kather JN, Weis CA, Bianconi F, Melchers SM, Schad LR, Gaiser T, Marx A, Zollner F: Multi-class texture analysis in colorectal cancer histology (2016), Scientific Reports (in press)

Contact

For questions, please contact:
Dr. Jakob Nikolas Kather
http://orcid.org/0000-0002-3730-5348
ResearcherID: D-4279-2015

Citation

@dataset{kather_2016_53169,
  author    = {Kather, Jakob Nikolas and Zöllner, Frank Gerrit and Bianconi, Francesco and Melchers, Susanne M and Schad, Lothar R and Gaiser, Timo and Marx, Alexander and Weis, Cleo-Aron},
  title     = {{Collection of textures in colorectal cancer histology}},
  month     = jun,
  year      = 2016,
  publisher = {Zenodo}
}
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