Article

On Bayesian image reconstruction from projections: uniform and nonuniform a priori source information

Dept. of Radiol., Duke Univ. Med. Center, Durham, NC
IEEE Transactions on Medical Imaging (impact factor: 3.64). 10/1989; DOI:10.1109/42.34711 pp.227 - 235
Source: IEEE Xplore

ABSTRACT A method that incorporates a priori uniform or nonuniform source
distribution probabilistic information and data fluctuations of a
Poisson nature is presented. The source distributions are modeled in
terms of a priori source probability density functions. Maximum a
posteriori probability solutions, as determined by a system of
equations, are given. Interactive Bayesian imaging algorithms for the
solutions are derived using an expectation maximization technique.
Comparisons of the a priori uniform and nonuniform Bayesian algorithms
to the maximum-likelihood algorithm are carried out using
computer-generated noise-free and Poisson randomized projections.
Improvement in image reconstruction from projections with the Bayesian
algorithm is demonstrated. Superior results are obtained using the a
priori nonuniform source distribution

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Keywords

Interactive Bayesian imaging algorithms
 
maximum-likelihood algorithm
 
nonuniform Bayesian algorithms
 
Poisson randomized projections
 
posteriori probability solutions
 
priori nonuniform source distribution
 
priori source probability density functions
 
priori uniform
 
solutions
 
source distributions
 
terms
 

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