Summary
This dataset consists of unenhanced Chest CT images of COVID-19 infection at the point of care in an outbreak setting with NIFTI files without annotations or bounding boxes. The images were retrospectively acquired after CT of patients with RT-PCR confirmation for the presence of SARS-CoV-2.NIFTI CT images were converted from DICOM images. CT reconstruction algorithm was soft tissue without intravenous contrast.
Patients presented to a health care setting with either symptoms &/or exposure to an infected patient, &/or travel history to an outbreak region. All patients had a positive RT-PCR for SARS-CoV-2 from a sample obtained within 1 day of the initial CT. There may be follow-up versions of this data set which include more sources of CT data or metadata, or annotated data to potentially make this dataset a useful tool and resource for developing algorithms for medical applications or data analysis challenges.
A multidisciplinary team trained several models using portions of this data set (along with manually annotated images and other data &/or other CT’s). A classification model derived in part from portions of this data (& other data) can be found at: https://wwwXXX or [DOI pubmed PMID].EMBARGOED FOR NOW / WILL PROVIDE WHEN EMBARGO LIFTED
Models partly derived from portions of this (& other) data may be found at: https://ngc.nvidia.com/catalog/resources/nvidia:clara:clara_ai_covid19_pipeline
A web-based research-only model (website for research use only) has CT drag-and-drop functionality. Upload of CT yields a return email that contains the results. This model is also partly derived from portions of this (& other) data: https://marketplace.arterys.com/model/nvidiacovidCT.
Acknowledgements
The Imaging AI in COVID team would like to acknowledge the following individuals who supported this multi-disciplinary multi-national team effort:
Peng An, Sheng Xu, Evrim B Turkbey, Stephanie A Harmon, Thomas H Sanford, Amel Amalou, Michael Kassin, Nicole Varble, Maxime Blain, Dilara Long, Dima Hammoud, Ashkan Malayeri, Elizabeth Jones, Holger Roth, Ziyue Xu, Dong Yang, Andriy Myronenko, Victoria Anderson, Mona Flores, Francesca Patella, Maurizio Cariati, Kaku Tamura, Hirofumi Obinata, Hitoshi Mori, Ulas Bagci, Daguang Xu, Hayet Amalou, Robert Suh, John Gallin, Steve Holland, Bruce Tromberg, Tom Misteli, Bill Dahut, Gianpaolo Carrafiello, Baris Turkbey, Bradford J Wood.
Data Access
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Detailed Description
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Citations & Data Usage Policy
Data Citation
An, P., Xu, S., Harmon, S.A., Turkbey, E.B., Sanford, T.H., Amalou, A., Kassin, M., Varble, N., Blain, M., Anderson,V., Patella, F., Carrafiello, G., Turkbey, B.T., Wood, B.J.: (2020) Chest CT Dataset for COVID-19 from Acute and Early SARS-CoV-2 Infection [Data set]. The Cancer Imaging Archive. https://doi.org/XXX.
Publication Citation
Publication under development.
Acknowledgement
TCIA Citation
Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7
Other Publications Using This Data
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Version 1 (Current): Updated 2020/mm/dd
Data Type | Download all or Query/Filter |
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Images (NIfTI, xx.x GB) | (Requires NBIA Data Retriever.) |
Clinical Data (CSV) | Link |