ABSTRACT
This chapter focuses on four of the most popular iterative algorithms: Algebraic Reconstruction Technique (ART), Simultaneous Iterative Reconstruction Technique (SIRT), Maximum Likelihood Expectation Maximization (MLEM), and Order Subset Expectation Maximization. ART is an implementation of the Kaczmarz’s method for solving linear systems. This reconstruction technique does not make any hypothesis on the underlying nature of the reconstructed data, i.e., it is purely algebraic. SIRT is considered as a variant of ART designed to produce smoother images. This feature comes at the expense of a slower convergence. The reason for this behaviour is that, unlike ART, the image is updated only once every projection is processed. MLEM is one of the most popular iterative reconstruction methods nowadays. The MLEM works under the hypothesis that the acquired data follows the Poisson distribution.
