SYNCHRONIZATION METHOD AND SYSTEM FOR SINGLE EVENT LIST TYPE DATA IN PET IMAGING

摘要

A method for synchronizing list-mode data of single events in a PET imaging includes: acquiring list-mode data of single events of each independent detection module, calculating a probability density of time intervals between occurrences of single events in detection module and setting initial parameters, determining detection starting time difference of each detection module with iterative peak searching and graded time window, and performing synchronization correction and coincidence discrimination on the single event data in each detection module based on the detection starting time difference. A system for synchronizing list-mode data of single events in a PET imaging includes: a data acquisition and frequency difference compensation module, an initial parameter setting module, a coarse time scale coincidence module, a fine time scale coincidence module and a data synchronization correction and coincidence discrimination module.

主权项

1. A method for synchronizing list-mode data of single events in a PET imaging, comprising:
step 1, acquiring and storing list-mode data of single events of each basic detection module working with a local reference clock source, and performing a frequency difference compensation on the list-mode data of the single events; step 2, calculating a probability density of time intervals between occurrences of single events in a single event data set acquired by each detection module, and setting respective initial parameters; step 3, performing, based on the parameters set in the step 2 and with an iterative peak searching, a synchronization correction and a coincidence peak searching on the single event data set acquired by each detection module; and determining a coarse estimated value of a detection starting time difference of each detection module; step 4, performing, based on the coarse estimated value of detection starting time difference obtained in the step 3 and with a graded time window, the synchronization correction and the coincidence peak searching on the single event data set acquired by each detection module; and determining a fine estimated value of the detection starting time difference of each detection module; and step 5, performing a weight accumulation on the coarse estimated value and the fine estimated value of the detection starting time difference, respectively obtained in the step 3 and the step 4, to determine the detection starting time difference of each detection module; and performing the synchronization correction and a coincidence discrimination on the single event data set acquired by each detection module, to obtain coincidence events.