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 implem...

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Bibliographic Details
Main Authors: Goddu, B. (Author), Guo, R. (Author), Haji-Valizadeh, H. (Author), Kucukseymen, S. (Author), Nezafat, R. (Author), Ngo, L.H (Author), Paskavitz, A. (Author), Pierce, P. (Author), Rodriguez, J. (Author), Tuyen, Y. (Author)
Format: Article
Language:English
Published: Frontiers Media S.A. 2021
Subjects:
artifact suppression
complex
deep learning
magnitude
real-time cine
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