Uncertainty in denoising of MRSI using low-rank methods.

ABSTRACT:

Purpose

Low-rank denoising of MRSI data results in an apparent increase in spectral SNR. However, it is not clear if this translates to a lower uncertainty in metabolite concentrations after spectroscopic fitting. Estimation of the true uncertainty after denoising is desirable for downstream analysis in spectroscopy. In this work, the uncertainty reduction from low-rank denoising methods based on spatiotemporal separability and linear predictability in MRSI are assessed. A new method for estimating metabolite concentration uncertainty after denoising is proposed. Automatic rank threshold selection methods are also assessed in simulated low SNR regimes.

Methods

Assessment of denoising methods is conducted using Monte Carlo simulation of proton MRSI data and by reproducibility

SUBMITTER: Clarke WT 

PROVIDER: S-EPMC7612041 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature