Abstract
A new method, based on a deformable shape-intensity model (DSM), was developed to improve the signal-to-noise ratio (SNR) of multidimensional magnetic resonance spectroscopic imaging (MRSI) data sets without affecting spectral lineshapes and linewidths. Improvements with DSM, compared to digital filters using conventional signal apodization, were demonstrated on both simulated and experimental in vivo
1
H MRS images from 22 cognitively normal (CN) elderly subjects and 25 patients with Alzheimer's disease (AD). Simulated MRSI data showed that DSM achieved superior noise suppression compared to a matched apodization filter. Experimental MRSI data showed that SNR could be increased 2.1-fold with DSM without distorting spectral resolution, thus maintaining all spectral features of the raw, unfiltered data. In conclusion, DSM should be used to achieve high SNR in reconstructing MRSI data.
