Blind deblurring reconstruction technique with applications in PET imaging

In this study, an empirical PET system model taking account for system blurring is developed and a blind iterative reconstruction scheme that estimate of both the actual image and the PSF of the system is derived based on the system model. Reconstruction images with higher quality can be acquired by applying the proposed reconstruction technique for both synthetic and experimental data. In the synthetic data study, the algorithm reduces image blurring and preserves the edges without introducing extra artifacts. The localized measurement shows that the performance of reconstruction image improved by up to 50%. In experimental studies, the contrast and quality of reconstruction is substantially improved. The proposed method shows promising in tumor localization and quantification.