Title :
Bayesian reconstructions from emission tomography data using a modified EM algorithm
fDate :
3/1/1990 12:00:00 AM
Abstract :
A novel method of reconstruction from single-photon emission computerized tomography data is proposed. This method builds on the expectation-maximization (EM) approach to maximum likelihood reconstruction from emission tomography data, but aims instead at maximum posterior probability estimation, which takes account of prior belief about smoothness in the isotope concentration. A novel modification to the EM algorithm yields a practical method. The method is illustrated by an application to data from brain scans
Keywords :
Bayes methods; brain; computerised tomography; radioisotope scanning and imaging; Bayesian reconstructions; brain scans; emission tomography data; isotope concentration smoothness; maximum likelihood reconstruction; maximum posterior probability estimation; modified EM algorithm; single-photon emission computerized tomography data; Application software; Bayesian methods; Blood flow; Cameras; Computed tomography; Image reconstruction; Isotopes; Maximum likelihood estimation; Pharmaceuticals; Single photon emission computed tomography;
Journal_Title :
Medical Imaging, IEEE Transactions on
