Iterative reconstruction of PET images using a high-overrelaxation single-projection algorithm

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Abstract
An iterative image reconstruction procedure is described which is able to calculate high-precision images within eight iterative steps. High initial overrelaxation parameters are used which drop down towards about one during continuing iteration. The parameters are determined pragmatically, postulating maximum gain of image quality during a sequence of iterative steps. Results with simulated and measured data show that parameters derived from one data set may be widely used for other data sets. The acceleration of iterative reconstruction achieved by the estimation of optimum overrelaxation parameters is important for large data sets, especially for fully 3D reconstruction.