Quantification of 1H–MRS signals based on sparse metabolite profiles in the time-frequency domain

Parto Dezfouli, M.A., Parto Dezfouli, M., Ahmadian, A. et al. (3 more authors) (2017) Quantification of 1H–MRS signals based on sparse metabolite profiles in the time-frequency domain. NMR in Biomedicine, 30 (2). e3675. ISSN 0952-3480

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: © Wiley, 2017.
Keywords: continuous wavelet transformation (CWT); MRS, quantification; sparse representation
Dates:
  • Published: 16 January 2017
  • Published (online): 4 January 2017
  • Accepted: 28 October 2016
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield)
Funding Information:
FunderGrant number
EUROPEAN COMMISSION - FP6/FP7VPH DARE - 601055
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/M006328/1
Depositing User: Symplectic Sheffield
Date Deposited: 31 Jan 2017 14:59
Last Modified: 31 Jan 2017 14:59
Published Version: https://doi.org/10.1002/nbm.3675
Status: Published
Publisher: Wiley
Refereed: Yes
Identification Number: https://doi.org/10.1002/nbm.3675

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