CVC-ClinicDB is a dataset for a semantic segmentation task. It is used in the medical industry.

The dataset consists of 612 images with 612 labeled objects belonging to 1 single class (polyp).

Images in the CVC-ClinicDB dataset have pixel-level semantic segmentation annotations. All images are labeled (i.e. with annotations). There are no pre-defined train/val/test splits in the dataset. Additionally, every image was recorded with its own video sequence. The dataset was released in 2015 by the CVC Computer Vision Center, UAB, Spain and Hospital Clinic Barcelona, Spain.

Copyright

The original images (i.e. the Images from folder ‘Original’) are property of Hospital Clinic, Barcelona, Spain

The annotations (i.e. Images from folder ‘Ground Truth’) are property of Computer Vision Center, Barcelona, Spain

Referencing

The use of this database is completely restricted for research and educational purposes. The use of this database is forbidden for commercial purposes.

If you use this database for your experiments please include the following reference:

Bernal, J., Sánchez, F. J., Fernández-Esparrach, G., Gil, D., Rodríguez, C., & Vilariño, F. (2015). WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians. Computerized Medical Imaging and Graphics, 43, 99-111.

Source

If you make use of the CVC-ClinicDB data, please cite the following reference:

@dataset{CVC-ClinicDB,
  author={Jorge Bernal and F. Javier Sánchez and Gloria Fernández-Esparrach and Debora Gil and Cristina Rodríguez and Fernando Vilariño},
  title={CVC-ClinicDB},
  year={2015},
  url={https://polyp.grand-challenge.org/CVCClinicDB/}
}

Source

Dataset CVC-ClinicDB can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='CVC-ClinicDB', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here.