Vector-extrapolated fast maximum likelihood estimation algorithms for emission tomography
Vector-extrapolated fast maximum likelihood estimation algorithms for emission tomography
复制标题
用于发射断层扫描的矢量外推快速最大似然估计算法
DOI：
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发表时间：
1992
期刊：
影响因子：
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通讯作者：
G. Krishna
中科院分区：
文献类型：
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作者：
N. Rajeevan;K. Rajgopal;G. Krishna
提出了一种新的用于发射计算机断层扫描（ECT）的快速最大似然估计（MLE）算法。在这些循环迭代算法中，将向量外推技术与基于梯度的MLE算法的迭代相结合，以加快基迭代的收敛速度。这导致获得指定质量的发射密度估计值所需的基本迭代的有效次数大大减少。数学理论背后的最小多项式和降秩向量外推技术，在发射层析成像的背景下，提出。这些外推技术在正电子发射层析成像系统中实现。新的算法通过计算机实验进行评估，并从模拟的幻影中进行测量。结果表明，在最小的额外计算量下，所提出的方法在重建方面有了很大的改善。
A new class of fast maximum-likelihood estimation (MLE) algorithms for emission computed tomography (ECT) is developed. In these cyclic iterative algorithms, vector extrapolation techniques are integrated with the iterations in gradient-based MLE algorithms, with the objective of accelerating the convergence of the base iterations. This results in a substantial reduction in the effective number of base iterations required for obtaining an emission density estimate of specified quality. The mathematical theory behind the minimal polynomial and reduced rank vector extrapolation techniques, in the context of emission tomography, is presented. These extrapolation techniques are implemented in a positron emission tomography system. The new algorithms are evaluated using computer experiments, with measurements taken from simulated phantoms. It is shown that, with minimal additional computations, the proposed approach results in substantial improvement in reconstruction.