Subspace denoising for CEST MRI with non-local low-rank constraint and spectral-smoothness regularization

Chemical exchange saturation transfer (CEST) is a powerful technique that enables non-invasive detection of endogenous metabolites in living tissues. Since the observed water signal is decreased due to the transfer of saturated spins, CEST imaging inherently suffers from low SNR, hence degrading accuracy and reproducibility. Inspired by the spatial-spectral correlation of CEST images, here we propose a Subapace denoising method with Non-Local Low-Rank constraint and Spectral-Smoothness regularization (SNLRSS) to diminish the noise, which improves the accuracy of subsequent quantitative analyses of CEST images.