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Abstract #2988

Comparison of low-rank denoising methods for accelerating the acquisition of 31P-MRSI

William T Clarke1 and Mark Chiew1
1Wellcome Centre for Integrative Neuroimaging, NDCN, University of Oxford, Oxford, United Kingdom

Two new low-rank denoising methods are compared to an existing low-rank denoising method in 31P-MRSI data of human skeletal muscle and brain. All three methods increase the SNR of the noisy data above that of high SNR data acquired in 4-times the duration. Denoising algorithm parameters are examined using a grid search. Optimal algorithm choice is dataset dependent and incorrect selection of parameters can bias spectra.

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