Fast Compressed Sensing of 3D Radial T<sub>1</sub> Mapping with Different Sparse and Low-Rank Models

Fast Compressed Sensing of 3D Radial T<sub>1</sub> Mapping with Different Sparse and Low-Rank Models

Knowledge of the relative performance of the well-known sparse and low-rank compressed sensing models with 3D radial quantitative magnetic resonance imaging acquisitions is limited. We use 3D radial T<sub>1</sub> relaxation time mapping data to compare the total variation, low-rank, and...

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Bibliographic Details
Main Authors: Antti Paajanen, Matti Hanhela, Nina Hänninen, Olli Nykänen, Ville Kolehmainen, Mikko J. Nissi
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Journal of Imaging
Subjects:
compressed sensing
T<sub>1</sub> relaxation
quantitative magnetic resonance imaging
regularization
image reconstruction
Online Access:https://www.mdpi.com/2313-433X/9/8/151

Internet

https://www.mdpi.com/2313-433X/9/8/151

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