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Title:

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

Document type:
Journal Article
Author(s):
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...     »
Journal title abbreviation:
Diagnostics (Basel)
Year:
2023
Journal volume:
13
Journal issue:
5
Fulltext / DOI:
doi:10.3390/diagnostics13050974
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/36900118
TUM Institution:
Professur für AI for Image-Guided Diagnosis and Therapy (Prof. Wiestler); Professur für Neuroradiologie (Prof. Zimmer)
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