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Published in: Magnetic Resonance Materials in Physics, Biology and Medicine 6/2014

01-12-2014 | Research Article

Spatio-temporal wavelet regularization for parallel MRI reconstruction: application to functional MRI

Authors: Lotfi Chaari, Philippe Ciuciu, Sébastien Mériaux, Jean-Christophe Pesquet

Published in: Magnetic Resonance Materials in Physics, Biology and Medicine | Issue 6/2014

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Abstract

Background

Parallel magnetic resonance imaging (MRI) is a fast imaging technique that helps acquiring highly resolved images in space/time. Its performance depends on the reconstruction algorithm, which can proceed either in the k-space or in the image domain.

Objective and methods

To improve the performance of the widely used SENSE algorithm, 2D regularization in the wavelet domain has been investigated. In this paper, we first extend this approach to 3D-wavelet representations and the 3D sparsity-promoting regularization term, in order to address reconstruction artifacts that propagate across adjacent slices. The resulting optimality criterion is convex but nonsmooth, and we resort to the parallel proximal algorithm to minimize it. Second, to account for temporal correlation between successive scans in functional MRI (fMRI), we extend our first contribution to 3D + \(t\) acquisition schemes by incorporating a prior along the time axis into the objective function.

Results

Our first method (3D-UWR-SENSE) is validated on T1-MRI anatomical data for gray/white matter segmentation. The second method (4D-UWR-SENSE) is validated for detecting evoked activity during a fast event-related functional MRI protocol.

Conclusion

We show that our algorithm outperforms the SENSE reconstruction at the subject and group levels (15 subjects) for different contrasts of interest (motor or computation tasks) and two parallel acceleration factors (\(R=2\) and \(R=4\)) on \(2\times 2\times 3\,\hbox{mm}^3\) echo planar imaging (EPI) images.
Appendix
Available only for authorised users
Footnotes
1
The overbar is used to distinguish the “true” data from a generic variable.
 
2
SENSE reconstruction implemented by the Siemens scanner, software ICE, VB 17.
 
5
Available in the xjView toolbox of SPM5.
 
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Metadata
Title
Spatio-temporal wavelet regularization for parallel MRI reconstruction: application to functional MRI
Authors
Lotfi Chaari
Philippe Ciuciu
Sébastien Mériaux
Jean-Christophe Pesquet
Publication date
01-12-2014
Publisher
Springer Berlin Heidelberg
Published in
Magnetic Resonance Materials in Physics, Biology and Medicine / Issue 6/2014
Print ISSN: 0968-5243
Electronic ISSN: 1352-8661
DOI
https://doi.org/10.1007/s10334-014-0436-5

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