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Titel:

Implementation of GAN-Based, Synthetic T2-Weighted Fat Saturated Images in the Routine Radiological Workflow Improves Spinal Pathology Detection.

Dokumenttyp:
Journal Article
Autor(en):
Schlaeger, Sarah; Drummer, Katharina; Husseini, Malek El; Kofler, Florian; Sollmann, Nico; Schramm, Severin; Zimmer, Claus; Kirschke, Jan S; Wiestler, Benedikt
Abstract:
(1) Background and Purpose: In magnetic resonance imaging (MRI) of the spine, T2-weighted (T2-w) fat-saturated (fs) images improve the diagnostic assessment of pathologies. However, in the daily clinical setting, additional T2-w fs images are frequently missing due to time constraints or motion artifacts. Generative adversarial networks (GANs) can generate synthetic T2-w fs images in a clinically feasible time. Therefore, by simulating the radiological workflow with a heterogenous dataset, this...     »
Zeitschriftentitel:
Diagnostics (Basel)
Jahr:
2023
Band / Volume:
13
Heft / Issue:
5
Volltext / DOI:
doi:10.3390/diagnostics13050974
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/36900118
TUM Einrichtung:
Professur für AI for Image-Guided Diagnosis and Therapy (Prof. Wiestler); Professur für Neuroradiologie (Prof. Zimmer)
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