Fast implementation of the single scatter simulation algorithm and its use in iterative image reconstruction of PET data

Abstract

In positron emission tomography (PET), scatter correction is usually performed prior to image reconstruction using a more or less exact model of the scatter processes. These models require estimates of the true activity and object density distributions of the imaged object. The problem is that these estimates are computed from measured data and, therefore, already contain scattered events. The purpose of this work was to overcome this problem by incorporating scatter characteristics directly into the process of iterative image reconstruction. This could be achieved by an optimized implementation of the single scatter simulation (SSS) algorithm, which results in a significant speed-up of the scatter estimation procedure. The scatter simulation was then included in the forward projection step of maximum likelihood image reconstruction. The results demonstrate that this approach leads to a more exact estimation of the scatter component which cannot be obtained by a simple sequential data processing strategy.