Parameter Estimation of Finite Mixtures Using the EM Algorithm and Information Criteria with Application to Medical linage

@inproceedings{Liang2004ParameterEO,
  title={Parameter Estimation of Finite Mixtures Using the EM Algorithm and Information Criteria with Application to Medical linage},
  author={Zhuolin Liang and R. J.K. and R. Edward Coleman},
  year={2004}
}
A method for parameter estimation in image classification or segmentation is studied within the statistical frame of finite mixture distributions. The method models an image as a finite mixture. Each mixture component corresponds to an image class. Each image class is characterized by parameters, such as the intensity mean, the standard deviation and the number of image pixels in that class. The method uses a maximum likelihood (ML) approach to estimate the parameters of each class, and employs… CONTINUE READING
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Showing 1-10 of 11 references

Simul - taneous Reconstruction , Segmentation , and Edge Enhancement of Relatively Piecewise Continuous Images with Intensity - Level Information

  • R. Jaszczak Liang, E. Coleman, V. Johnson
  • 1991

" 3 D Phantom to Simulate Cerebral Blood Flow and Metabolic Images for PET

  • M. Wax, T. Kailath
  • 1990

H . Akaike , " A New Look at the Statistical Model Identification

  • A. Smith D. Titterington
  • Statistical Analysis of Finite Mixture…
  • 1985

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