BAYESIAN RECONSTRUCTIONS FROM EMISSION TOMOGRAPHY DATA USING A MODIFIED EM ALGORITHM
BAYESIAN RECONSTRUCTIONS FROM EMISSION TOMOGRAPHY DATA USING A MODIFIED EM ALGORITHM
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DOI：
10.1109/42.52985
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发表时间：
1990-03-01
影响因子：
10.6
通讯作者：
GREEN, PJ
中科院分区：
文献类型：
--
作者：
GREEN, PJ
提出了一种由单光子发射计算机层析成像数据进行重建的新方法。这种方法建立在期望最大化(EM)方法的基础上，从发射断层扫描数据中进行最大似然重建，但目标是最大后验概率估计，该估计考虑了关于同位素浓度平滑的先验信念。对EM算法进行了一种新的改进，得到了一种实用的方法。通过对脑部扫描数据的应用说明了该方法。
A novel method of reconstruction from single-photon emission computerized tomography data is proposed. This method builds on the expectation-maximization (EM) approach to maximum likelihood reconstruction from emission tomography data, but aims instead at maximum posterior probability estimation, which takes account of prior belief about smoothness in the isotope concentration. A novel modification to the EM algorithm yields a practical method. The method is illustrated by an application to data from brain scans.<>