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In this paper we present an efficient implementation of the EM algorithm for estimating multivariate gaussian mixture model parameters in the context of local-neighborhood image texture analysis. We illustrate its application in a study case of mass detection in mammography, providing a detailed description of a feasible and efficient implementation. Our proposed method overcomes numerical variable underflow problems by means of logarithmic and exponential manipulations and saves computational time using a look up table approach. We reduced computation time to 57.14% with respect to direct computation, achieving numerical conditions for convergence.