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Magnetic Resonance Materials in Physics, Biology and Medicine

Published in:

01-12-2016 | Research Article

Denoising of MR spectroscopic imaging data using statistical selection of principal components

Authors: Abas Abdoli, Radka Stoyanova, Andrew A. Maudsley

Published in: Magnetic Resonance Materials in Physics, Biology and Medicine | Issue 6/2016

Abstract

Objectives

To evaluate a new denoising method for MR spectroscopic imaging (MRSI) data based on selection of signal-related principal components (SSPCs) from principal components analysis (PCA).

Materials and methods

A PCA-based method was implemented for selection of signal-related PCs and denoising achieved by reconstructing the original data set utilizing only these PCs. Performance was evaluated using simulated MRSI data and two volumetric in vivo MRSIs of human brain, from a normal subject and a patient with a brain tumor, using variable signal-to-noise ratios (SNRs), metabolite peak areas, Cramer-Rao bounds (CRBs) of fitted metabolite peak areas and metabolite linewidth.

Results

In simulated data, SSPC determined the correct number of signal-related PCs. For in vivo studies, the SSPC denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared to the original data and two other methods for denoising. The method also performed very well in preserving the spectral linewidth and peak areas. However, this method performs better for regions that have larger numbers of similar spectra.

Conclusion

The proposed SSPC denoising improved the SNR and metabolite quantification uncertainty in MRSI, with minimal compromise of the spectral information, and can result in increased accuracy.

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Title: Denoising of MR spectroscopic imaging data using statistical selection of principal components
Authors: Abas Abdoli
Radka Stoyanova
Andrew A. Maudsley
Publication date: 01-12-2016
Publisher: Springer Berlin Heidelberg
Published in: Magnetic Resonance Materials in Physics, Biology and Medicine / Issue 6/2016
Print ISSN: 0968-5243
Electronic ISSN: 1352-8661
DOI: https://doi.org/10.1007/s10334-016-0566-z

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Denoising of MR spectroscopic imaging data using statistical selection of principal components

Abstract

Objectives

Materials and methods

Results

Conclusion

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Abstract

Objectives

Materials and methods

Results

Conclusion

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