Almeida, Silvia D. http://orcid.org/0000-0002-4133-1194
Norajitra, Tobias
Lüth, Carsten T.
Wald, Tassilo
Weru, Vivienn
Nolden, Marco
Jäger, Paul F.
von Stackelberg, Oyunbileg
Heußel, Claus Peter
Weinheimer, Oliver
Biederer, Jürgen
Kauczor, Hans-Ulrich
Maier-Hein, Klaus
Funding for this research was provided by:
Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg (32-5400/58/3)
Helmholtz Imaging
Deutsches Krebsforschungszentrum (DKFZ)
Article History
Received: 5 October 2023
Revised: 13 November 2023
Accepted: 11 December 2023
First Online: 27 December 2023
Declarations
:
: The scientific guarantor of this publication is Prof. Dr. Klaus Maier-Hein.
: The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
: One of the authors has significant statistical expertise: Vivienn Weru, Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
: Written informed consent was obtained from all subjects (patients) in this study.
: Institutional Review Board approval was obtained.
: The used cohorts (COPDGene and COSYCONET) are open access, therefore have been reported in several previous studies, including our own:Almeida, S.D. et al (2023). cOOpD: reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations. In: Greenspan, H., et al Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023. Lecture Notes in Computer Science, vol 14224. Springer, Cham. .
: • retrospective• observational• multicenter study