Noise estimation in parallel MRI: GRAPPA and SENSE

Abstract Parallel imaging methods allow to increase the acquisition rate via subsampled acquisitions of the k -space. SENSE and GRAPPA are the most popular reconstruction methods proposed in order to suppress the artifacts created by this subsampling. The reconstruction process carried out by both m...

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Bibliographic Details
Published in:Magnetic resonance imaging 2014-04, Vol.32 (3), p.281-290
Main Authors: Aja-Fernández, Santiago, Vegas-Sánchez-Ferrero, Gonzalo, Tristán-Vega, Antonio
Format: Article
Language:English
Subjects:
Computer Simulation
Data Interpretation, Statistical
GRAPPA
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Magnetic Resonance Imaging - instrumentation
Magnetic Resonance Imaging - methods
Models, Statistical
Multiple-coil
Noise estimation
Parallel imaging
Phantoms, Imaging
Radiology
Reproducibility of Results
SENSE
Sensitivity and Specificity
Signal-To-Noise Ratio
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Summary:Abstract Parallel imaging methods allow to increase the acquisition rate via subsampled acquisitions of the k -space. SENSE and GRAPPA are the most popular reconstruction methods proposed in order to suppress the artifacts created by this subsampling. The reconstruction process carried out by both methods yields to a variance of noise value which is dependent on the position within the final image. Hence, the traditional noise estimation methods – based on a single noise level for the whole image – fail. In this paper we propose a novel methodology to estimate the spatial dependent pattern of the variance of noise in SENSE and GRAPPA reconstructed images. In both cases, some additional information must be known beforehand: the sensitivity maps of each receiver coil in the SENSE case and the reconstruction coefficients for GRAPPA.
ISSN:0730-725X
1873-5894
DOI:10.1016/j.mri.2013.12.001