DocumentCode :
948518
Title :
A (μ + λ) evolutionary algorithm for reconstruction of SPECT data
Author :
Knoll, Peter ; Kenny, Bob ; Mirzaei, Siroos ; Koriska, Karl ; Köhn, Horst ; Neumann, Martin
Author_Institution :
Dept. of Nucl. Medicine, Univ. of Vienna, Austria
Volume :
6
Issue :
6
fYear :
2002
fDate :
12/1/2002 12:00:00 AM
Firstpage :
533
Lastpage :
541
Abstract :
Algorithms used to reconstruct single photon emission computed tomography (SPECT) data are based on one of two principles: filtered back projection or iterative methods. In this paper, an evolution strategy (ES) was applied to reconstruct transaxial slices of SPECT data. Evolutionary algorithms are stochastic global search methods that have been used successfully for many kinds of optimization problems. The newly developed reconstruction algorithm consisting of μ parents and λ children uses a random principle to readjust the voxel values, whereas other iterative reconstruction methods use the difference between measured and simulated projection data. The (μ + λ)-ES was validated against a test image, a heart, and a Jaszczak phantom. The resulting transaxial slices show an improvement in image quality, in comparison to both the filtered back projection method and a standard iterative reconstruction algorithm.
Keywords :
computerised tomography; genetic algorithms; image reconstruction; medical image processing; radioisotope imaging; single photon emission computed tomography; SPECT data; evolutionary algorithm; image reconstruction; medical image processing; nuclear medicine; optimization; single-photon emission-computerized tomography; voxel values; Evolutionary computation; Image reconstruction; Iterative algorithms; Iterative methods; Optimization methods; Reconstruction algorithms; Search methods; Single photon emission computed tomography; Stochastic processes; Testing;
fLanguage :
English
Journal_Title :
Evolutionary Computation, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-778X
Type :
jour
DOI :
10.1109/TEVC.2002.806743
Filename :
1134121
Link To Document :
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