Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction

Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction

BackgroundSimultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image reconstruction but result in high noise level. Alternatively, ite...

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Bibliographic Details
Main Authors: Naledi Lenah Adam, Grzegorz Kowalik, Andrew Tyler, Ronald Mooiweer, Alexander Paul Neofytou, Sarah McElroy, Karl Kunze, Peter Speier, Daniel Stäb, Radhouene Neji, Muhummad Sohaib Nazir, Reza Razavi, Amedeo Chiribiri, Sébastien Roujol
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-07-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
magnetic resonance imaging
myocardial perfusion
simultaneous multi-slice
image reconstruction
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2024.1350345/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2024.1350345/full

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