A novel Fourier-based perspective to analyze and compensate for corruption in arterial spin labeling MRI

Abstract

A new perspective in Fourier domain to understand the ASL signal and compensate for corruption artifacts is proposed. The averaged perfusion-subtraction image corresponds to a single frequency component and the other frequency components could be interpreted as non-perfusion signals. In this viewpoint, the multiple corruptions could be compensated by finding the optimal perfusion frequency component to minimize the zigzag amplitude in the non-perfusion signals. The proposed compensation reduced the corruption without eliminating any measured data, preserving SNR. This new perspective would open up the possibility of processing the ASL signal in the Fourier domain rather than the time domain.