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.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Liang Z,Jaszczak R,Greer Kdoi
10.1109/42.34711subject
Has Abstractpub_date
1989-01-01 00:00:00pages
227-35issue
3eissn
0278-0062issn
1558-254Xjournal_volume
8pub_type
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