This technology is a strategy to improve PET scanner sensitivity by normalizing and correcting sorted IDS events. The correction calculation, determined during a calibration step, can then be applied to a coincidence data set generated by the scanner to yield meaningful coincidence information.
In calibration, a radiation source is uniformly exposed to all detector pairs in a PET scanner. Double coincidences and IDS coincidences are acquired until enough measurements have been collected to achieve statistical significance in both data sets. IDS events are then sorted and represented, for example, in an LOR histogram. The number of IDS events sorted to a particular LOR is then divided by the average number of IDS events for all of the LORs in the scanner to calculate IDS normalization values for each LOR. In contrast to other normalization methods, which only generate normalization value for double coincidences, this method provides a second set of normalization values for IDS events. During the PET scan, sets of double coincidences and IDS coincidences are collected and stored as separate LOR histogram. The corresponding normalization (from calibration) will be applied independently to each data set. After correction, the data sets are added together to provide normalized information for accurate image reconstruction.