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Correlated spectroscopic imaging of calf muscle in three spatial dimensions using group sparse reconstruction of undersampled single and multichannel data.


ABSTRACT: PURPOSE:To implement a 5D (three spatial?+?two spectral) correlated spectroscopic imaging sequence for application to human calf. THEORY AND METHODS:Nonuniform sampling was applied across the two phase encoded dimensions and the indirect spectral dimension of an echo planar-correlated spectroscopic imaging sequence. Reconstruction was applied that minimized the group sparse mixed ?2,1-norm of the data. Multichannel data were compressed using a sensitivity map-based approach with a spatially dependent transform matrix and utilized the self-sparsity of the individual coil images to simplify the reconstruction. RESULTS:Single channel data with 8× and 16× undersampling are shown in the calf of a diabetic patient. A 15-channel scan with 12× undersampling of a healthy volunteer was reconstructed using 5 virtual channels and compared to a fully sampled single slice scan. Group sparse reconstruction faithfully reconstructs the lipid cross peaks much better than ?1 minimization. CONCLUSION:COSY spectra can be acquired over a 3D spatial volume with scan time under 15 min using echo planar readout with highly undersampled data and group sparse reconstruction.

SUBMITTER: Wilson NE 

PROVIDER: S-EPMC4619112 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Correlated spectroscopic imaging of calf muscle in three spatial dimensions using group sparse reconstruction of undersampled single and multichannel data.

Wilson Neil E NE   Burns Brian L BL   Iqbal Zohaib Z   Thomas M Albert MA  

Magnetic resonance in medicine 20150918 5


<h4>Purpose</h4>To implement a 5D (three spatial + two spectral) correlated spectroscopic imaging sequence for application to human calf.<h4>Theory and methods</h4>Nonuniform sampling was applied across the two phase encoded dimensions and the indirect spectral dimension of an echo planar-correlated spectroscopic imaging sequence. Reconstruction was applied that minimized the group sparse mixed ℓ2,1-norm of the data. Multichannel data were compressed using a sensitivity map-based approach with a  ...[more]

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