Comparison of Complex k-Space Data and Magnitude-Only for Training of Deep Learning–Based Artifact Suppression for Real-Time Cine MRI

Comparison of Complex k-Space Data and Magnitude-Only for Training of Deep Learning–Based Artifact Suppression for Real-Time Cine MRI

Propose: The purpose of this study was to compare the performance of deep learning networks trained with complex-valued and magnitude images in suppressing the aliasing artifact for highly accelerated real-time cine MRI.Methods: Two 3D U-net models (Complex-Valued-Net and Magnitude-Net) were impleme...

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Bibliographic Details
Main Authors: Hassan Haji-Valizadeh, Rui Guo, Selcuk Kucukseymen, Yankama Tuyen, Jennifer Rodriguez, Amanda Paskavitz, Patrick Pierce, Beth Goddu, Long H. Ngo, Reza Nezafat
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Physics
Subjects:
real-time cine
artifact suppression
deep learning
complex
magnitude
Online Access:https://www.frontiersin.org/articles/10.3389/fphy.2021.684184/full

Internet

https://www.frontiersin.org/articles/10.3389/fphy.2021.684184/full

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