Simultaneous frequency and phase corrections of single-shot MRS data using cross-correlation

Motivation: Preprocessing of MRS data is important in order to improve the spectral quality. Goal(s): Here we propose a novel approach to simultaneously correct for frequency and phase drifts using cross-correlation technique. Approach: Random frequency and phase offsets were added to a previously acquired STEAM human data at 7T at two different noise levels. Results: Results show that the proposed technique can accurately correct for both small and large frequency (<50 Hz) and phase drifts (±40 deg) even at low SNR levels. The technique was successfully demonstrated in a noisy MRS dataset acquired from a small volume-of-interest in the mouse brain. Impact: A fast and robust technique which accurately correct for both small and large frequency and phase shifts in MRS data.