Evaluation of a New Regularization Prior for 3-D PET Reconstruction Including PSF Modeling

The response of a PET system can be described by its characteristic Point Spread Function (PSF) representing the spatial degradation of a point source due to physical effects and system design. If the PSF is accounted for in the reconstruction algorithm, better image quality and spatial resolution may be achieved. Unfortunately, a common behaviour of unregularized iterative reconstruction techniques is represented by the increase of noise as the iterations proceed, while—on the other hand—a high number of iterations is usually needed to recover a significant percentage of the signal and to reach convergence, especially when resolution modelling is used in the reconstruction to recover the degraded signal. Moreover, a recognized effect of PSF-based reconstructions is the overenhancement of sharp transitions (edges) in the reconstructed images.