Skip to main content

Datasets

Standard Dataset

BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients with Extension Part II

Citation Author(s):
Maria de la Iglesia Vayá (Unidad Mixta de Imagen Biomédica FISABIO-CIPF)
Jose Manuel Saborit-Torres (Unidad Mixta de Imagen Biomédica FISABIO-CIPF)
Joaquim Angel Montell Serrano (Unidad Mixta de Imagen Biomédica FISABIO-CIPF)
Elena Oliver-Garcia (Unidad Mixta de Imagen Biomédica FISABIO-CIPF)
Marisa Caparrós Redondo (Unidad Mixta de Imagen Biomédica FISABIO-CIPF)
Antonio Pertusa (Universidad de Alicante, Spain)
Aurelia Bustos (Medbravo)
Miguel Cazorla (Hospital San Juan de Alicante, Spain)
Joaquin Galant (Universidad de Alicante, Spain)
Xavier Barber (Universidad Miguel Hernández, Spain)
Domingo Orozco-Beltrán (Universidad Miguel Hernández, Spain)
Francisco García-García (Unidad Mixta de Imagen Biomédica FISABIO-CIPF & Bioinformatics & Biostatistics Unit Principe Felipe Research Center, Valencia, Spain)
Germán González (Universidad de Alicante, Spain & Sierra Research SL)
Jose María Salinas (Unidad Mixta de Imagen Biomédica FISABIO-CIPF & Hospital San Juan de Alicante, Spain)
Submitted by:
Marisa Caparros
Last updated:
DOI:
10.21227/r5db-8b17
Data Format:
Links:
No Ratings Yet

Abstract

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, 5 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. These iterations of the database include 21342 CR, 34829 DX and 7918 CT studies.

Project/Equipment funded by Consellería de Sanitat Universal i Salut Pública (Generalitat Valenciana, Spain) and the EU Operational Program of the European Regional Development Fund (ERDF) for the Valencian Community 2014-2020, within the framework of the REACT-EU programme, as the Union's response to the COVID-19 pandemic

 



 

Instructions:

Once all the compressed files have been downloaded, use 00_extract_data.sh for their correct decompression. For more information, you could see the links on this page.

Finally, this second part is completed.

 

Dataset Files

DOCUMENTATION

DATASET SCRIPTS