Statistical models for PET and SPECT data.
Statistical models for PET and SPECT data.
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DOI：
10.1177/096228029400300102
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发表时间：
1994-01-01
影响因子：
2.3
通讯作者：
Kay, J
中科院分区：
文献类型：
--
作者：
Kay, J
本文概述了过去十年左右发射断层扫描的统计发展。我们讨论投影数据建模的统计方面并定义加性泊松回归模型。这导致使用最大似然法作为估计患者身体给定区域内的潜在同位素浓度的方法，并使用 EM 算法来计算重建。使用贝叶斯技术解决了调节最大似然解的需要。概述了用于计算正则化解的多种算法。讨论了参数估计问题并提到了一些悬而未决的问题。
This article outlines the statistical developments that have taken place in emission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data and define the additive Poisson regression model. This leads to the use of the method of maximum likelihood as a means of estimating the underlying isotope concentration within a given region of a patient's body, and to the use of the EM algorithm to compute the reconstruction. The need for the regulation of the maximum likelihood solution is tackled using Bayesian techniques. A number of algorithms for the computation of regularized solutions are outlined. The issue of parameter estimation is discussed and some open issues are mentioned.