Synthetic T2-weighted fat sat based on a generative adversarial network shows potential for scan time reduction in spine imaging in a multicenter test dataset

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Title:: Synthetic T2-weighted fat sat based on a generative adversarial network shows potential for scan time reduction in spine imaging in a multicenter test dataset
Document type:: Zeitschriftenaufsatz
Author(s):: Schlaeger, Sarah ; Drummer, Katharina ; El Husseini, Malek ; Kofler, Florian ; Sollmann, Nico ; Schramm, Severin ; Zimmer, Claus ; Wiestler, Benedikt ; Kirschke, Jan S.
Keywords:: Imaging Informatics and Artificial Intelligence ; Magnetic resonance imaging ; Spine ; Artificial intelligence
Journal title:: European Radiology
Year:: 2023
Journal volume:: 33
Journal issue:: 8
Pages contribution:: 5882-5893
Fulltext / DOI:: doi:10.1007/s00330-023-09512-4
Publisher:: Springer Berlin Heidelberg
E-ISSN:: 1432-1084
Date of publication:: 16.03.2023
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