A semi-automated quality assurance tool for cardiovascular magnetic resonance imaging: application to outlier detection, artificial intelligence evaluation and trainee feedback
Lazy Luna, as a semi-automated quality assurance tool, is applicable to several quality assurance application cases in CMR.
Authors
- Maximilian Fenski (ORCID: https://orcid.org/0000-0002-5943-305X)
- Richard Hickstein
- Anja Hennemuth (ORCID: https://orcid.org/0000-0002-0737-7375)
- Jan Gröschel (ORCID: https://orcid.org/0000-0002-7268-9041)
- Darian Viezzer (ORCID: https://orcid.org/0000-0002-1599-3557)
- Clemens Ammann (ORCID: https://orcid.org/0000-0002-5962-4008)
- Jeanette Schulz‐Menger (ORCID: https://orcid.org/0000-0003-3100-1092)
- Edyta Błaszczyk (ORCID: https://orcid.org/0000-0001-7370-1690)
- Thomas Hadler (ORCID: https://orcid.org/0000-0002-6151-6858)
- Leonhard Grassow
- Ralf-Felix Trauzeddel
- Steffen Lange
- Hadil Saad (ORCID: https://orcid.org/0000-0001-8574-644X)
- Johanna Kuhnt
Institutions
- Darmstadt University of Applied Sciences (DE)
- Humboldt-Universität zu Berlin (DE)
- Deutsches Herzzentrum der Charité (DE)
- German Centre for Cardiovascular Research (DE)
- Fraunhofer Institute for Digital Medicine (DE)
- Deutsches Herzzentrum München (DE)
- Helios Hospital Berlin-Buch (DE)
- Franklin University (US)
- Freie Universität Berlin (DE)
- Charité - Universitätsmedizin Berlin (DE)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1186/s12911-025-03271-6
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00