A Preliminary Study on Optimization-Based Image Reconstruction from Sparse, List-Mode TOF-PET Data

In this study, we investigated TOF-PET systems with reduced density of detector modules possibly to lower detector cost for given volume coverage. The TOF-PET image is designed as a solution specified by an optimization program. As the optimization program depends critically on the TOF-PET configuration of a specific detector-module distribution, TOF-PET configurations with different detector-module distributions lead to different optimization programs. We develop a Chambolle and Pock (CP) algorithm to reconstruct images through solving these optimization programs, thus enabling effectively the investigation and prototyping of TOF-PET configurations of reduced densities of detector modules. The results of our study suggest that TOF-PET configurations with certain sparsely distributed detector modules can yield image quality comparable to that obtained with the current TOF-PET scanner with densely distributed detector modules.