Algebraic PET image reconstruction with pre-computed reconstruction operators using subsets of sensitivity functions

Algebraic reconstruction methods have been successfully used to improve quality of positron emission tomography (PET) images by accurate modeling of measurement system, but they have computational burden. The authors propose a fast PET image reconstruction method based on an algebraic technique. In this method, reconstruction operators are pre-computed approximately using subsets of sensitivity functions. The subsets contain the sensitivity functions that contribute significantly to each point to be reconstructed. The proposed method was applied to simulated data and experimental data for the ECAT EXACT HR+ (Siemens/CTI) scanner operating in 2D mode. These results show that the proposed method produces images with almost the same quality as the conventional algebraic methods do and has a similar computation time to the filtered backprojection method