Simultaneous Identification of Noise and Estimation of Noise Standard Deviation in MRI

Cheng Guan Koay¹, Evren zarslan¹, Carlo Pierpaoli¹

Analysis of MRI data usually entails a series of processing steps. One of these steps is noise assessment, which includes both the identification of noise and the estimation of noise variance (standard deviation). In MRI, the identification of noise has received less attention than has the estimation of noise variance. Here, we propose a novel approach to simultaneously identify noise and estimate the standard deviation of noise from a data structure commonly used in MRI. Experimental data acquired using an 8-channel phased array coil were used to investigate the feasibility and the stability of the proposed technique.