The Maximum Likelihood Estimator Method of Image Reconstruction: Its Fundamental Characteristics and their Origin
The Maximum Likelihood Estimator Method of Image Reconstruction: Its Fundamental Characteristics and their Origin
复制标题
图像重建的最大似然估计方法:其基本特征及其起源
DOI:
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发表时间:
1988
期刊:
影响因子:
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通讯作者:
E. Veklerov
中科院分区:
文献类型:
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作者:
J. Llacer;E. Veklerov
In this paper we review our recent work in characterizing the image reconstruction properties of the MLE algorithm. We have studied its convergence properties and confirmed the onset of image deterioration, which is a function of the number of counts in the source. By modulating the weight given to projection tubes with high numbers of counts with respect to those with low numbers of counts in the reconstruction process, we have confirmed that image deterioration is due to an attempt by the algorithm to match projection data tubes with high numbers of counts too closely to the iterative image projections. We have also developed a stopping rule for the algorithm that tests the hypothesis that a reconstructed image could have given the initial projection data in a manner consistent with the underlying assumption of Poisson distributed variables. The rule has been applied to two mathematically generated phantoms with success and to a third phantom with “exact” (no statistical fluctuations) projection data with results which confirm our understanding of the fundamental process of iterative image reconstruction. We conclude that the behavior of the target functions whose extrema are sought in iterative schemes is more important in the early stages of the reconstruction than in the later stages, when the extrema are being approached but the results are in contradiction with the Poisson nature of the measurement.