Title :
Bayesian estimation of transmission tomograms using local optimization operations
Author :
Sauer, Ken ; Bouman, Charles
Author_Institution :
Dept. of Electr. Eng., Notre Dame Univ., IN, USA
Abstract :
A method for nondifferentiable optimization in MAP (maximum a posteriori) estimation of computed tomographs is presented. This problem arises in the application of a Markov random field image model with absolute value potential function. The algorithm uses local optimization operations, operating in alternating iterations on pixels, and on elements in an intermediate segmentation of the estimate.<>
Keywords :
Bayes methods; computerised tomography; optimisation; Bayesian estimation; Markov random field image model; absolute value potential function; algorithm; computed tomographs; elements; iterations; local optimization operations; maximum a posteriori estimation; medical diagnostic imaging; nondifferentiable optimization; pixels; segmentation; transmission tomograms; Bayesian methods; Cost function; Image reconstruction; Image segmentation; Markov random fields; Maximum likelihood detection; Maximum likelihood estimation; Optimization methods; Pixel; Tomography;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference, 1991., Conference Record of the 1991 IEEE
Conference_Location :
Santa Fe, NM, USA
Print_ISBN :
0-7803-0513-2
DOI :
10.1109/NSSMIC.1991.259283
