MP-PCA and Low-rank noise-reduction in 1H-FID-MRSI data in the rat brain at 14.1T

Abstract

1H-MRSI is highly challenging and the constant appetite for higher spatial resolution leads to increased search for post-processing methods aiming to reduce the noise variance in 1H-MRSI. The aim of the present study was to implement and test the feasibility of two noise-reduction techniques on preclinical 14.1T fast 1H-FID-MRSI datasets: the MP-PCA based denoising and the low-rank TGV reconstruction. Our results are promising showing an enormous potential of the two noise-reduction techniques towards novel and fast MRSI developments. Further studies will be performed to evaluate if the “apparent” increase in spectral SNR translates in true lower uncertainty in metabolite concentrations.