BIMCV-COVID19, Datasets related to COVID19’s pathology course
NOTICE (20th October 2020): Due to the high demand of these datasets, it is recommended downloading the data through WebDAV protocol (please, see more details in each dataset webpage).
NOTICE (July 9 2021): Due to a power outage for BSC maintenance, their servers may not be available from July 19 2021 at 07:00h until July 26 at 16:00h
BIMCV-COVID19+: a large annotated dataset of RX and CT images of COVID19 patients
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, 23 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 7377 CR, 9463 DX and 6687 CT studies.
DOI: 10.21227/w3aw-rv39
Data availability
Use of the BIMCV-COVID19 is free to all researchers. Researchers seeking to use the full Clinical Database must formally request access. By requesting access the user agrees that (1) he/she will not share the data, (2) he/she will make no attempt to reidentify individuals.
The BIMCV-COVID19, although de-identified, still contains information regarding the clinical care of patients, and must be treated with appropriate respect. Researchers seeking to use the full Clinical Database must formally request access.
B2DROP is supported as part of the EUDAT Collaborative Data Infrastructure services (www.eudat.eu). The B2DROP instance used for this work is provided by BSC-CNS.
Dataset Research Use Agreement
Please, read BIMCV-COVID19 Dataset Research Use Agreement before download.
BIMCV-COVID19-: a large annotated dataset of RX and CT images of no COVID19 patients
BIMCV-COVID19- dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of no 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.
DOI: 10.21227/m4j2-ap59
Data availability
Use of the BIMCV-COVID19 is free to all researchers. Researchers seeking to use the full Clinical Database must formally request access. By requesting access the user agrees that (1) he/she will not share the data, (2) he/she will make no attempt to reidentify individuals.
The BIMCV-COVID19, although de-identified, still contains information regarding the clinical care of patients, and must be treated with appropriate respect. Researchers seeking to use the full Clinical Database must formally request access.
Dataset Research Use Agreement
Please, read BIMCV-COVID19 Dataset Research Use Agreement before download.
BIMCV-COVID19-PADCHEST, a reorganization of PadChest dataset related to COVID-19’s pathology course
BIMCV-COVID-19 «the Covid 19 images dataset will come as soon as possible, be attent». The Padchest-pneumonia dataset, here (visit our github).
Following common strategies and initiatives emerged from the scientific community at international level, a series of actions are being carried out within the Valencia Region Image Bank (BIMCV) that combines data from the PadChest dataset with future datasets based on COVID-19 pathology to provide the open scientific community with data of clinical-scientific value that helps early detection of COVID-19.
Medical Imaging Example of COVID-19 Rx from medRxiv preprint doi
Data availability
Use of the BIMCV-COVID19 is free to all researchers. Researchers seeking to use the full Clinical Database must formally request access. By requesting access the user agrees that (1) he/she will not share the data, (2) he/she will make no attempt to reidentify individuals.
The BIMCV-COVID19, although de-identified, still contains information regarding the clinical care of patients, and must be treated with appropriate respect. Researchers seeking to use the full Clinical Database must formally request access.
Dataset Research Use Agreement
Please, read BIMCV-COVID19 Dataset Research Use Agreement before download.
SIIM-FISABIO-RSNA COVID-19 Detection
Covid-Pneumonia Detection Challenge to Identify and localize COVID-19 abnormalities on chest radiographs
The BIMCV-COVID19 dataset is shared in order to contribute to the Covid-Pneumonia Kaggle Challenge promoted by the Society for Imaging Informatics in Medicine (SIIM) and the Radiological Society of North America (RSNA) for identification and localisation COVID-19 in torax radiography.
We encourage all data scientists and AI engineers around the world to participate in this Kaggle.
Terms of Use and Attribution for the BIMCV-COVID19
Participants may access and use these de-identified imaging datasets and annotations for the purposes of academic research and education, and other commercial or non-commercial purposes as long as they agree to the Terms and Conditions described in this link.
Contact
If you want to know more about the project, or contact the research team, write to us.