Kay J
Department of Statistics, University of Glasgow, UK.
Stat Methods Med Res. 1997 Mar;6(1):55-75. doi: 10.1177/096228029700600105.
This article outlines the statistical developments that have taken place in the use of the EM algorithm in emission and transmission tomography during the past decade or so. We discuss the statistical aspects of the modelling of the projection data for both the emission and transmission cases and define the relevant probability models. This leads to the use of the method of maximum likelihood as a means of estimating the relevant unknown parameters within a given region of a patient's body and to the use of the EM algorithm to compute the reconstruction. Various different types of EM algorithm are discussed, including the SAGE algorithms of Fessler and Hero. The limitations of the EM algorithm, per se, are covered and the need for regularization is stressed. A number of different methods for penalizing the likelihood are described and a number of algorithms for the computation of the penalized EM reconstruction are discussed.
本文概述了在过去十年左右的时间里,期望最大化(EM)算法在发射和透射断层扫描中的统计发展情况。我们讨论了发射和透射情况下投影数据建模的统计方面,并定义了相关的概率模型。这导致使用最大似然法作为估计患者身体给定区域内相关未知参数的一种手段,并使用EM算法进行重建计算。讨论了各种不同类型的EM算法,包括费斯勒(Fessler)和赫罗(Hero)的空间交替广义期望最大化(SAGE)算法。阐述了EM算法本身的局限性,并强调了正则化的必要性。描述了一些惩罚似然的不同方法,并讨论了一些用于计算惩罚后的EM重建的算法。