Density Estimation Using Modified Expectation-Maximization algorithm for a Linear Combination of Gaussians (TP-L4)

Author(s) : Aly Farag (University of Louisville, USA) Ayman El-Baz (University of Louisville, USA) Georgy Gimel' farb (University of Auckland, New Zealand)

Abstract : We propose a modified Expectation-Maximization algorithm that approximates an empirical probability density function of scalar data with a linear combination of Gaussians (LCG). Due to both positive and negative components, the LCG approximates inter-class transitions more accurately than a conventional mixture of only positive Gaussians. Experiments in segmenting multi-modal medical images show the proposed LCG-approximation results in more adequate region borders.

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