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:
Wed, 05/31/2023 - 03:24
DOI:
10.21227/r5db-8b17
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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.

 

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Required data for education purpose

Submitted by Vijay Ithape on Fri, 05/12/2023 - 05:08

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