On Modeling the Tissue Response from Ultrasonic B-scan Images

We model tissue as a collection of point scatterers embedded in a uniform media, and show that the higher-order statistics (HOS) of the scatterer spacing distribution can be estimated from digitized RF scan line segments and be used in obtaining tissue signatures. We assume that RF echoes are non-Gaussian, on the grounds of empirical/theoretical justifications presented in works such as [25], [6], [3], [24] and [27]. Based on our model for tissue microstructure, we develop schemes for the estimation of resolvable periodicity as well as correlations among nonperiodic scatterers. Using higher-order statistics of the scattered signal, we define as tissue "color" a quantity that describes the scatterer spatial correlations, show how to evaluate it from the higher-order correlations of the digitized RF scan line segments, and investigate its potential as a tissue signature. The tools employed, i.e., higher-order statistics, were chosen as the most appropriate ones because they suppress Gau..