Timing calibration in PET is of great importance for improving time resolution. In this paper, we present a new computational strategy for the framework based upon the low rank principles, solved through the ADMM. The linear equations of time delay is constructed using a point source or a phantom. The low rank property captures spatiotemporal correlation of noise-corrupted measurement. Experiments with Monte Carlo simulation and real data have been conducted with very promising results, as validated through comparison to some existing methods.
