Influence of noise correlation in multiple-coil statistical models with sum of squares reconstruction

Abstract

Noise in the composite magnitude signal from multiple-coil systems is usually assumed to follow a noncentral χ distribution when sum of squares is used to combine images sensed at different coils. However, this is true only if the variance of noise is the same for all coils, and no correlation exists between them. We show how correlations may be obviated from this model if effective values are considered. This implies a reduced effective number of coils and an increased effective variance of noise. In addition, the effective variance of noise becomes signal-dependent.