Hybrid sparse regularization for magnetic resonance spectroscopy

Andrea Laruelo, Lotfi Chaari, Hadj Batatia, Soleakhena Ken, Ben Rowland, Anne Laprie, Jean-Yves Tourneret

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Magnetic resonance spectroscopy imaging (MRSI) is a powerful non-invasive tool for characterising markers of biological processes. This technique extends conventional MRI by providing an additional dimension of spectral information describing the abnormal presence or concentration of metabolites of interest. Unfortunately, in vivo MRSI suffers from poor signal-to-noise ratio limiting its clinical use for treatment purposes. This is due to the combination of a weak MR signal and low metabolite concentrations, in addition to the acquisition noise. We propose a new method that handles this challenge by efficiently denoising MRSI signals without constraining the spectral or spatial profiles. The proposed denoising approach is based on wavelet transforms and exploits the sparsity of the MRSI signals both in the spatial and frequency domains. A fast proximal optimization algorithm is then used to recover the optimal solution. Experiments on synthetic and real MRSI data showed that the proposed scheme achieves superior noise suppression (SNR increase up to 60%). In addition, this method is computationally efficient and preserves data features better than existing methods.

Original languageEnglish
Title of host publication2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
PublisherIEEE
Pages6768-6771
Number of pages4
ISBN (Electronic)9781457702167
DOIs
Publication statusPublished - 26 Sep 2013
Event35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2013 - Osaka, Japan
Duration: 3 Jul 20137 Jul 2013

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology Society
ISSN (Print)1094-687X
ISSN (Electronic)1558-4615

Conference

Conference35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2013
Abbreviated titleEMBC 2013
Country/TerritoryJapan
CityOsaka
Period3/07/137/07/13

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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