Comput Math Methods Med - A generalized gamma mixture model for ultrasonic tissue characterization.

Tópicos

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Resumo

Several statistical models have been proposed in the literature to describe the behavior of speckles. Among them, the Nakagami distribution has proven to very accurately characterize the speckle behavior in tissues. However, it fails when describing the heavier tails caused by the impulsive response of a speckle. The Generalized Gamma (GG) distribution (which also generalizes the Nakagami distribution) was proposed to overcome these limitations. Despite the advantages of the distribution in terms of goodness of fitting, its main drawback is the lack of a closed-form maximum likelihood (ML) estimates. Thus, the calculation of its parameters becomes difficult and not attractive. In this work, we propose (1) a simple but robust methodology to estimate the ML parameters of GG distributions and (2) a Generalized Gama Mixture Model (GGMM). These mixture models are of great value in ultrasound imaging when the received signal is characterized by a different nature of tissues. We show that a better speckle characterization is achieved when using GG and GGMM rather than other state-of-the-art distributions and mixture models. Results showed the better performance of the GG distribution in characterizing the speckle of blood and myocardial tissue in ultrasonic images.

Resumo Limpo

sever statist model propos literatur describ behavior speckl among nakagami distribut proven accur character speckl behavior tissu howev fail describ heavier tail caus impuls respons speckl general gamma gg distribut also general nakagami distribut propos overcom limit despit advantag distribut term good fit main drawback lack closedform maximum likelihood ml estim thus calcul paramet becom difficult attract work propos simpl robust methodolog estim ml paramet gg distribut general gama mixtur model ggmm mixtur model great valu ultrasound imag receiv signal character differ natur tissu show better speckl character achiev use gg ggmm rather stateoftheart distribut mixtur model result show better perform gg distribut character speckl blood myocardi tissu ultrason imag

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