Multicriterion maximum entropy image reconstruction from projections
A solution algorithm for the image reconstruction problem with three criteria, maximum entropy, minimum nonuniformity and peakedness, and least square error between the original projection data and projection due to reconstruction is presented. Theoretical results of precedence properties which are...
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Published in | IEEE transactions on medical imaging Vol. 11; no. 1; pp. 70 - 75 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
New York, NY
IEEE
01.03.1992
Institute of Electrical and Electronics Engineers |
Subjects | |
Online Access | Get full text |
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Summary: | A solution algorithm for the image reconstruction problem with three criteria, maximum entropy, minimum nonuniformity and peakedness, and least square error between the original projection data and projection due to reconstruction is presented. Theoretical results of precedence properties which are respected by all noninferior solutions are first derived. These precedence properties are then incorporated into a multiple-criteria optimization framework to improve the computational efficiency. Comparisons of the new algorithm to the MART and MENT algorithms are carried out using computer-generated noise-free and Gaussian noisy projections. Results of the computational experiment and the efficiency of the multiobjective entropy optimization algorithm (MEOA) are reported.< > |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0278-0062 1558-254X |
DOI: | 10.1109/42.126912 |