COVIDGR datasets

Datasets of X-Ray imaging for detection of COVID-19. More information about these datasets

Dataset	Class distribution	Download	Cite
COVIDGR-1.0	426 COVID, 426 normal	⤓ Download	Citation

COVIDGR 1.0

Under a close collaboration with an expert radiologist team of the Hospital Universitario San Cecilio, the COVIDGR-1.0 dataset of patients' anonymized X-ray images has been built. 852 images have been collected following a strict labeling protocol. They are categorized into 426 positive cases and 426 negative cases. Positive images correspond to patients who have been tested positive for COVID-19 using RT-PCR within a time span of at most 24h between the X-ray image and the test. Every image has been taken using the same type of equipment and with the same format: only the posterior-anterior view is considered. More information about image distribution:

Class	#images	women	men	severities
negative	426	239	187
positive	426	190	236	Normal-PCR+: 76, Mild: 100, Moderate: 171, Severe: 79

Cite COVIDGR 1.0 as

@misc{tabik2020covidgr,
    title={COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images},
    author={S. Tabik and A. Gómez-Ríos and J. L. Martín-Rodríguez and I. Sevillano-García and M. Rey-Area and D. Charte and E. Guirado and J. L. Suárez and J. Luengo and M. A. Valero-González and P. García-Villanova and E. Olmedo-Sánchez and F. Herrera},
    year={2020},
    eprint={2006.01409},
    archivePrefix={arXiv},
    primaryClass={eess.IV}
}