Finite Series-Expansion Reconstruction Methods

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Series-expansion reconstruction methods made their first appearance in the scientific literature and in the CT scanner industry around 1970. Great research efforts have gone into them since but many questions still wait to be answered. These methods, synonymously known as algebraic methods, iterative algorithms, or optimization theory techniques, are based on the discretization of the image domain prior to any mathematical analysis and thus are rooted in a completely different branch of mathematics than the transform methods which are discussed in this issue by Lewitt [51]. How is the model set up? What is die methodology of the approach? Where does mathematical optimization theory enter? What do these reconstruction algorithms look like? How are quadratic optimization, entropy optimization, and Bayesian analysis used in image reconstruction? Finally, why study series expansion methods if transform methods are so much faster? These are some of the questions that are answered in this paper.

Original languageEnglish
Pages (from-to)409-419
Number of pages11
JournalProceedings of the IEEE
Issue number3
StatePublished - Mar 1983
Externally publishedYes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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