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Measuring the distribution of major brain tissues, including the gray matter, white matter and cerebrospinal fluid (CSF), using magnetic resonance imaging (MRI) has attracted extensive research efforts. Many brain MRI image segmentation methods in the literature are based on the Gaussian mixture model (GMM), which however is not strictly followed due to the intrinsic complex nature of MRI data and...
As an essential step in brain studies, measuring the distribution of major brain tissues, including gray matter, white matter and cerebrospinal fluid (CSF), using magnetic resonance imaging (MRI) has attracted extensive research efforts over the past years. Many brain tissue differentiation methods resulted from these efforts are based on the finite statistical mixture model, which however, in spite...
The variational expectation maximization (VEM) algorithm has recently been increasingly used to replace the expectation maximization (EM) algorithm in Gaussian mixture model (GMM) based statistical image segmentation. However, the VEM algorithm, similar to its traditional counterpart, suffers from the sensitiveness to initializations, and hence is prone to be trapped into local minima. In this paper,...
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