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The statistics of envelope of high-frequency ultrasonic backscatter signals from in vivo normal human dermis and subcutaneous fat were studied. The capability of six probability distributions (Rayleigh, Rician, K, Nakagami, Weibull, and Generalized Gamma) to model empirical envelope data was studied using the Kolmogorov-Smirnov (KS) goodness of fit statistic. The parameters of all the distributions were obtained using the maximum likelihood method. It was found that the Generalized Gamma distribution with two shape parameters provided the best fit among all the distributions in terms of the KS goodness of fit. The K and Weibull distributions also modeled the envelope statistics well. The Rayleigh and Rician distributions provided poorer fits. The parameters of the Generalized Gamma distribution, however, showed a larger variability than those of the other distributions. The intersubject variability in the estimated parameters of all the distributions was found to be comparable to the intrasubject variability. Fat was seen to exhibit significantly more pre-Rayleigh behavior compared to the dermis. The parameters of the Generalized Gamma distribution also showed significant differences between the dermis at the forearm and fingertip regions.
Raju et al. (Mon,) studied this question.