Preliminary Patient Study of TV-Constrained Image Reconstruction from Low-Statistics List-Mode TOF-PET Data

Advanced clinical positron-emission tomography (PET) scanners exploit time-of-flight (TOF) information of annihilation photons for improving PET imaging performance, and image reconstruction from TOF-PET data remains an active research topic. In the study, we investigate optimization-based image reconstruction from list-mode TOF-PET data collected with a clinical PET system employing the digital silicon photomultiplier (SiPM) technology. The reconstruction problem is formulated as an image-TV-constrained data-fidelity-minimization problem, and a primal-dual algorithm is tailored for image reconstruction through solving the optimization problem. In an attempt to evaluate the reconstruction performance, we have carried out studies on images reconstructed from data of patient subjects. A focus of the work centers on investigating image reconstruction from data containing different amounts of photon accounts. Results of the study reveal that the proposed algorithm can yield image reconstruction with suppressed noise level and increased axial coverage over that obtained in conventional reconstructions.