Abstract
In the past different analytical expressions have been derived to describe the correlation curve /spl rho/(/spl Delta/x) of two ultrasonic images which are created from a set of subapertures for spatial compounding or a set of subbands for frequency compounding. We show that both speckle reduction with spatial compounding (SC) and with frequency compounding (FC) can be modeled by a Gaussian shaped correlation curve of the kind /spl rho/(/spl Delta/x)=exp(-/spl Delta/x/sup 2///spl alpha/), where /spl Delta/x represents either the relative shift between neighboring subapertures or neighboring subbands and the parameter /spl alpha/ is a constant which describes the inherent properties of the two compounding algorithms. With our experiments the parameter /spl alpha/ is estimated individually for SC and FC and the model is used to determine the optimum number of subimages to obtain maximum lesion detectability with a predefined loss in resolution. The results are compared with experimental data.
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