Generating Virtual Short Tau Inversion Recovery (STIR) Images from T1- and T2-Weighted Images Using a Conditional Generative Adversarial Network in Spine Imaging

Generating Virtual Short Tau Inversion Recovery (STIR) Images from T1- and T2-Weighted Images Using a Conditional Generative Adversarial Network in Spine Imaging

Short tau inversion recovery (STIR) sequences are frequently used in magnetic resonance imaging (MRI) of the spine. However, STIR sequences require a significant amount of scanning time. The purpose of the present study was to generate virtual STIR (vSTIR) images from non-contrast, non-fat-suppresse...

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Bibliographic Details
Main Authors: Johannes Haubold, Aydin Demircioglu, Jens Matthias Theysohn, Axel Wetter, Alexander Radbruch, Nils Dörner, Thomas Wilfried Schlosser, Cornelius Deuschl, Yan Li, Kai Nassenstein, Benedikt Michael Schaarschmidt, Michael Forsting, Lale Umutlu, Felix Nensa
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Diagnostics
Subjects:
spine
magnetic resonance imaging
computing
medical informatics
machine learning
Online Access:https://www.mdpi.com/2075-4418/11/9/1542

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