Optimization of the Algorithm for the Implementation of Point Spread Function in the 3D-OSEM Reconstruction Algorithm Based on the List-Mode Micro PET Data

Positron emission tomography (PET) is a popular research topic. People are becoming more interested in PET images as they become widely available. However, the partial volume effect (PVE) remains one of most influential factors causing resolution to degrade. It possible reduce this PVE and achieve better image quality by measuring modeling point spread function (PSF) then accounting for it inside reconstruction algorithm. In work, we examined response characteristics MetisTM PET/CT system acquiring 22Na source at different locations field view (FOV) scanner reconstructing with small pixel size obtain their radial, tangential, axial full-width half maximum (FWHM). An image-based model PSF was obtained fitting asymmetric two-dimensional Gaussians on images. This determined FWHM three directions integrated into three-dimensional ordered subsets expectation maximization (3D-OSEM) algorithm based list-mode format form new PSF-OSEM We used both algorithms reconstruct source, Derenzo phantom, mouse performed qualitative quantitative analyses. study, reduced about 0.67 mm, phantom reconstructed had visual effects. At same time, analysis results were than original 3D-OSEM experiment, analyses showed that imaging Our show adding helps improve satisfy criteria.