An information-theoretic approach to estimating ultrasound backscatter characteristics

Analysis of backscatter in the ultrasound echo envelope, in conjunction with ultrasound B-scans, can provide important information for tissue characterization and pathology diagnosis. Statistical models have often proven useful in modeling backscatter. In this paper, an innovative approach to backscatter analysis based on generalized entropies and neural function approximation is presented. Entropy measures are shown to provide accurate estimates of scatterer density, regularity, and SNR of the amplitude distribution. Specific scattering distributions need not be assumed. Experimental results on ground truth envelopes show that generalized entropies can be used to accurately estimate backscatter properties.