Matched filter for event identification and processing in PET

Positron Emission Tomography (PET) is a technology that can image the spatial and temporal distribution of radio-labeled biomolecules in-vivo. It is dependent on the coincidence detection of photons emitted due to the annihilation of positrons. Most PET scanners use constant fraction discriminators (CFD) to confirm detector triggering. Following this, a blocking time window is used to allow processing of individual events. However, if a second (or more) event interacts with the detectors within this blocking time window, this method will not be capable to accurately identify its timing or energy, while the energy information for the first event is lost. Both energy and timing of all events are necessary for accurate event detection and localization. In these cases and without a method to identify individual events collected within the blocking time window, all events within the blocking window must be rejected, resulting in a real loss in sensitivity. The information loss in these situations is a significant problem when using high activity sources due to the high probability of event pile-up. To address this issue, we examined the performance of a matched filter when applied to raw pulses obtained from a pulse library derived from the PETBox system. Here, we compare the performance of the matched filter to CFD for event detection, positioning and timing. In addition, we show preliminary results from a real-time digital implementation of the matched filter on the PETBox FPGA. Preliminary results indicate that the matched filter can significantly improve the fidelity of the detection of true events at high count rates, as compared to conventional CFD, while event timing is somewhat compromised for the matched filter.