Regularization-based SENSE reconstruction and choice of regularization parameter

The acceleration in Parallel MRI is achieved by reducing the number of phase encode steps during data acquisition. SENSE is a Parallel MRI algorithm which reconstructs the fully sampled MR images. Standard SENSE is limited by the noise amplification especially for higher acceleration factors. The g...

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Published inConcepts in magnetic resonance. Part A, Bridging education and research Vol. 44; no. 2; pp. 67 - 73
Main Authors Omer, Hammad, Qureshi, Mahmood, Dickinson, Robert J.
Format Journal Article
LanguageEnglish
Published Blackwell Publishing Ltd 01.03.2015
Subjects
parallel MRI
regularization
SENSE
Tikhonov regularization
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Summary:The acceleration in Parallel MRI is achieved by reducing the number of phase encode steps during data acquisition. SENSE is a Parallel MRI algorithm which reconstructs the fully sampled MR images. Standard SENSE is limited by the noise amplification especially for higher acceleration factors. The g ‐Factor represents the noise amplification during the process of image reconstruction and it varies from pixel‐to‐pixel. Regularization based SENSE reconstruction uses prior knowledge to improve the quality of the reconstructed image. A method based on the use of g ‐Factor as a regularization parameter in the Tikhonov regularized SENSE reconstruction is proposed. The results show significant improvement in the reconstructed images and computation time. © 2015 Wiley Periodicals, Inc. Concepts Magn Reson Part A 44A: 67–73, 2015.
Bibliography:istex:8D5EA5727B80E2803C7436C622D69301A9288F92
ark:/67375/WNG-XKPC723X-3
ArticleID:CMRA21328
ISSN:1546-6086
1552-5023
DOI:10.1002/cmr.a.21328