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Licenses and Acknowledgements

This work would not have been possible without the efforts of many researchers to make COVID-19 CT data publicly accessible. In particular, we construct the COVIDx CT dataset from the following publicly available data sources:

  • CNCB 2019 Novel Coronavirus Resource (2019nCoVR) AI Diagnosis Dataset
  • CT Images in COVID-19 (TCIA)
    • Data Citation: An P, Xu S, Harmon SA, Turkbey EB, Sanford TH, Amalou A, Kassin M, Varble N, Blain M, Anderson V, Patella F, Carrafiello G, Turkbey BT, Wood BJ (2020). CT Images in Covid-19 [Data set]. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/tcia.2020.gqry-nc81
    • Publication Citation: Harmon SA, Sanford TH, Xu S, Turkbey EB, Roth H, Xu Z, Yang D, Myronenko A, Anderson V, Amalou A, Blain M, Kassin M, Long D, Varble N, Walker SM, Bagci U, Ierardi AM, Stellato E, Plensich GG, Franceschelli G, Girlando C, Irmici G, Labella D, Hammoud D, Malayeri A, Jones E, Summer RM, Choyke PL, Xu D, Flores M, Tamura K, Obinata H, Mori H, Patella F, Cariati M, Carrafiello G, An P, Wood BJ, Turkbey B (2020). Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets. Nature Communications. DOI: https://doi.org/10.1038/s41467-020-17971-2
    • 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. (2013) The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, pp 1045-1057. DOI: https://doi.org/10.1007/s10278-013-9622-7
    • Acknowledgement: The Multi-national NIH Consortium for CT AI in COVID-19. The annotation of the dataset was made possible through the joint work of Children's National Hospital, NVIDIA and National Institutes of Health for the COVID-19-20 Lung CT Lesion Segmentation Grand Challenge.
    • License: Attribution 4.0 International (CC BY 4.0)
  • COVID-19 CT Lung and Infection Segmentation Dataset
  • LIDC-IDRI
    • Data Citation: Armato III, SG; McLennan, G; Bidaut, L; McNitt-Gray, MF; Meyer, CR; Reeves, AP; Zhao, B; Aberle, DR; Henschke, CI; Hoffman, Eric A; Kazerooni, EA; MacMahon, H; van Beek, EJR; Yankelevitz, D; Biancardi, AM; Bland, PH; Brown, MS; Engelmann, RM; Laderach, GE; Max, D; Pais, RC; Qing, DPY; Roberts, RY; Smith, AR; Starkey, A; Batra, P; Caligiuri, P; Farooqi, Ali; Gladish, GW; Jude, CM; Munden, RF; Petkovska, I; Quint, LE; Schwartz, LH; Sundaram, B; Dodd, LE; Fenimore, C; Gur, D; Petrick, N; Freymann, J; Kirby, J; Hughes, B; Casteele, AV; Gupte, S; Sallam, M; Heath, MD; Kuhn, MH; Dharaiya, E; Burns, R; Fryd, DS; Salganicoff, M; Anand, V; Shreter, U; Vastagh, S; Croft, BY; Clarke, LP. (2015). Data From LIDC-IDRI. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2015.LO9QL9SX
    • Publication Citation: Armato SG 3rd, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, Zhao B, Aberle DR, Henschke CI, Hoffman EA, Kazerooni EA, MacMahon H, Van Beeke EJ, Yankelevitz D, Biancardi AM, Bland PH, Brown MS, Engelmann RM, Laderach GE, Max D, Pais RC, Qing DP, Roberts RY, Smith AR, Starkey A, Batrah P, Caligiuri P, Farooqi A, Gladish GW, Jude CM, Munden RF, Petkovska I, Quint LE, Schwartz LH, Sundaram B, Dodd LE, Fenimore C, Gur D, Petrick N, Freymann J, Kirby J, Hughes B, Casteele AV, Gupte S, Sallamm M, Heath MD, Kuhn MH, Dharaiya E, Burns R, Fryd DS, Salganicoff M, Anand V, Shreter U, Vastagh S, Croft BY. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans. Medical Physics, 38: 915--931, 2011. DOI: https://doi.org/10.1118/1.3528204
    • 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. (2013) The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, pp 1045-1057. DOI: https://doi.org/10.1007/s10278-013-9622-7
    • Acknowledgement: The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study.
    • License: Attribution 3.0 Unported (CC BY 3.0)
  • COVID-CTSet
  • Radiopaedia.org
  • Integrative CT Images and Clinical Features for COVID-19 (iCTCF)
  • COVID-CT-MD
    • Publication Citation: Afshar, P., Heidarian, S., Enshaei, N. et al. COVID-CT-MD, COVID-19 computed tomography scan dataset applicable in machine learning and deep learning. Sci Data 8, 121 (2021). https://doi.org/10.1038/s41597-021-00900-3
    • License: Unknown; assumed to be open access based on publication
  • Stony Brook University COVID-19 Positive Cases (COVID-19-NY-SBU)
    • Data Citation: Saltz, J., Saltz, M., Prasanna, P., Moffitt, R., Hajagos, J., Bremer, E., Balsamo, J., & Kurc, T. (2021). Stony Brook University COVID-19 Positive Cases [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.BBAG-2923
    • 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. (2013) The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, pp 1045-1057. DOI: https://doi.org/10.1007/s10278-013-9622-7
    • License: Attribution 4.0 International (CC BY 4.0)
  • Study of thoracic CT in COVID-19 (STOIC)
    • Publication Citation: Marie-Pierre Revel, Samia Boussouar, Constance de Margerie-Mellon, Inès Saab, Thibaut Lapotre, Dominique Mompoint, Guillaume Chassagnon, Audrey Milon, Mathieu Lederlin, Souhail Bennani, Sébastien Molière, Marie-Pierre Debray, Florian Bompard, Severine Dangeard, Chahinez Hani, Mickaël Ohana, Sébastien Bommart, Carole Jalaber, Mostafa El Hajjam, Isabelle Petit, Laure Fournier, Antoine Khalil, Pierre-Yves Brillet, Marie-France Bellin, Alban Redheuil, Laurence Rocher, Valérie Bousson, Pascal Rousset, Jules Grégory, Jean-François Deux, Elisabeth Dion, Dominique Valeyre, Raphael Porcher, Léa Jilet, and Hendy Abdoul. Study of Thoracic CT in COVID-19: The STOIC Project. Radiology 2021 301:1, E361-E370. https://doi.org/10.1148/radiol.2021210384
    • License: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
  • MosMedData