Image Resolution Improvement Based on Sinogram Super-Resolution in PET

One of the limits of PET imaging is the low spatial resolution due to a predetermined detector width. To overcome this limit, we may increase the number of samples by using the wobbling motion. Since the line spread function (LSF) of the sinogram is determined by the detector width, however, the increase of the number of samples is not sufficient to improve the sinogram resolution. In this paper, based on oversampled data obtained from the wobbling motion, we propose a novel and efficient super-resolution (SR) scheme for the sinogram. Since the proposed SR scheme adopts the penalized expectation maximization (EM) algorithm, it guarantees non-negative values of the super-resolved sinogram data. Through the experiments, we demonstrate that the proposed SR scheme can noticeably improve the spatial image resolution.