Multicriterion cross-entropy minimization approach to positron emission tomographic imaging.
A multicriterion cross-entropy minimization approach to positron emission tomographic (PET) imaging is described. An unexplored multicriterion cross-entropy optimization algorithm based on weighted-sum scalarization is used to solve this problem. The efficacy of the algorithm is compared with that of the single-criterion optimization algorithm and the convolution backprojection method for image reconstruction from computer-generated projection data and Siemens PET scanner data. The algorithms described have been implemented on a PIII/686 microcomputer.
Wang
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Department of Biomedical Engineering, Zhejiang University, Hangzhou, China. yuanmei@usa.net
D000465:Algorithms; D003198:Computer Simulation; D019277:Entropy; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical; D014055:Tomography, Emission-Computed