Regularized one-pass list-mode EM algorithm for high resolution 3D PET image reconstruction into large arrays

Abstract

High resolution 3D PET scanners with high count rate performance, such as the quad-HIDAC, place new demands on image reconstruction algorithms due to the large quantities of high precision list-mode data which are produced. Therefore a reconstruction algorithm is required which can, in a practical time frame, reconstruct into very large image arrays (submillimetre voxels, which range over a large field of view) whilst preferably retaining the precision of the data. This work presents an algorithm which meets these demands: Regularized One-Pass List-mode EM (ROPLE). The algorithm operates directly on list-mode data, passes through the data once only, accounts for finite resolution effects in the system model and also includes regularization. The algorithm performs multiple image updates during its single pass through the list-mode data, corresponding to the number of subsets that the data have been split into. The algorithm has been assessed using list-mode data from a quad-HIDAC, and is compared to the analytic reconstruction method 3D RP.