Preliminary Study Of Tv-Constrained-Likelihood-Maximization Image Reconstruction From List-Mode Tof-Pet Data

Time-of-flight (TOF) positron emission tomography (PET) has the potential to yield images with improved quality by comparison to conventional PET. Numerous iterative algorithms have been investigated for image reconstruction in TOF-PET. In this work, we investigate optimization based image reconstruction from list-mode TOF-PET data collected with a digital PET system under clinical evaluation. Specifically, the reconstruction problem is formulated as an image-TV-constrained data-likelihood-maximization program. We then tailor a primal-dual algorithm to reconstruct the image through solving the problem. In an attempt to evaluate the reconstruction design, we have performed investigation on reconstructions from list-mode TOF-PET data in real-data study in which data were collected from the standard IEC phantom by use of the digital PET system. Results reveal that the proposed algorithm yields image reconstruction with improved image quality in terms of visualization and standard quantitative metrics, than does the conventional reconstruction algorithm under the study conditions.