Full-spectrum comparison of denoising algorithms for real-time magnetic resonance imaging acoustics

Abstract

Using real-time MRI acoustic data, we employ two methods of signal denoising (DLWP and CS-SNG) to conduct a preliminary comparison between noisy, denoised, and noiseless data. The acoustic data collected in the MRI serve as the noisy, “baseline” group. Data collected from the same speakers in a sound-attenuated environment served as the noiseless, “ground truth.” We calculate acoustic power across the frequency spectrum in 32, 64, 128, and 256 bin experiments and perform k-means clustering on the first three principal components to compare the output of the denoising algorithms to the ground-truth and noisy data. Results show a quantitative difference between the denoising methods, through their different affinities for clusters associated with reference group labels. The groupings indicate that the CS-SNG data are better suited for establishing a map between the visual data from the MRI and the acoustic output because of its association with the noiseless data and its distinction from the noisy group. Si...