Hybrid Genetic and Variational Expectation-Maximization Algorithm for Gaussian-Mixture-Model-Based Brain MR Image Segmentation

The expectation-maximization (EM) algorithm has been widely applied to the estimation of Gaussian mixture model (GMM) in brain MR image segmentation. However, the EM algorithm is deterministic and intrinsically prone to overfitting the training data and being trapped in local optima. In this paper,...

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Veröffentlicht in:	IEEE transactions on information technology in biomedicine Jg. 15; H. 3; S. 373 - 380
Hauptverfasser:	Tian, GuangJian, Xia, Yong, Zhang, Yanning, Feng, Dagan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2011
Schlagworte:	Algorithms Bayes Theorem Brain - anatomy & histology Brain modeling Estimation Female Gallium Gaussian mixture model (GMM) genetic algorithm (GA) Genetic algorithms Humans Image Processing, Computer-Assisted - methods Image resolution Image segmentation Information technology Magnetic Resonance Imaging - methods Male MRI Normal Distribution variational Bayes inference
ISSN:	1089-7771, 1558-0032, 1558-0032
Online-Zugang:	Volltext
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