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Tissue mixture characterization in the presence of MRI inhomogeneity by the em algorithm

  • Stony Brook University
  • City University of New York
  • Air Force Medical University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a model-based approach to correct for both partial volume effect and inhomogeneity in segmenting tissue mixtures inside each voxel of magnetic resonance images. A maximum a posteriori probability (MAP) solution is sought. In calculating the solution, the wellknown expectation maximization (EM) algorithm is employed. The models of data likelihood and Markov priors for tissue mixture and bias field in establishing this MAP-EM framework are described in details. A preliminary test is presented.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesII1140-II1143
StatePublished - 2006
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: May 14 2006May 19 2006

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Conference

Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Country/TerritoryFrance
CityToulouse
Period05/14/0605/19/06

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