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README.md
BIMCV-COVID19 + dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G ( IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV). The findings are mapped onto standard Unified Medical Language System (UMLS) terminology and they cover a wide spectrum of thoracic entities, contrasting with the much more reduced number of entities annotated in previous datasets. Images are stored in high resolution and entities are localized with anatomical labels in a Medical Imaging Data Structure (MIDS) format. In addition, 10 images were annotated by a team of expert radiologists to include semantic segmentation of radiographic findings. Moreover, extensive information is provided, including the patient's demographic information, type of projection and acquisition parameters for the imaging study, among others. This first iteration of the database includes 1380 CX, 885 DX and 163 CT studies.
Citation
Please use the following citation when referencing the dataset:
@article{de2020bimcv,
title={BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients.},
author={de la Iglesia Vay{\'a}, Maria and Saborit, Jos{\'e} Manuel and Montell, Joaquim Angel
and Pertusa, Antonio and Bustos, Aurelia and Cazorla, Miguel and Galant, Joaquin and Barber,
Xavier and Orozco-Beltr{\'a}n, Domingo and Garc{\'\i}a-Garc{\'\i}a, Francisco and others},
journal={arXiv preprint arXiv:2006.01174},
year={2020}
}
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