The Bayesian approach that employs the concepts of cliques and line sites in its Gibbs prior provides the potential of realistic and objective characterization of boundaries between different regions exhibiting intensity variations in the reconstructed images. In this work, we develop an improved Bayesian approach for accurate detection of boundaries by introducing symmetric cliques and new types of line sites as well as a new calculation scheme. This improved Bayesian approach has been applied to positron emission tomography data from both computer simulations and patient studies. The results demonstrate that the new cliques, line sites, and calculation scheme can enhance the boundary detectability of the Bayesian approach and yield realistic boundaries and hence improved reconstructed images.

Date Published: 18 August 1995
PDF: 10 pages
Proc. SPIE 2622, Optical Engineering Midwest '95, (18 August 1995); doi: 10.1117/12.216885

Published in SPIE Proceedings Vol. 2622:
Optical Engineering Midwest '95
Rudolph P. Guzik, Editor(s)