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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,...
PET-CT provides aligned anatomical (CT) and functional (PET) images in a single scan, and has the potential to improve brain PET image segmentation, which can in turn improve quantitative clinical analyses. We propose a statistical segmentation algorithm that incorporates the prior anatomical knowledge represented by probabilistic brain atlas into the variational Bayes inference to delineate gray...
Dual-modality PET-CT imaging has been prevalently used as an essential diagnostic tool for monitoring treatment response in malignant disease patients. However, evaluation of treatment outcomes in serial scans by visual inspecting multiple PET-CT volumes is time consuming and laborious. In this paper, we propose an automated algorithm to detect the occurrence and changes of hot-spots in intro-subject...
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