Sixtieth annual meeting of the canadian organization of medical physicists and the canadian college of physicists in medicine
Poster — Thur Eve — 07: Simultaneous reconstruction of both true and scattered coincidences using a Generalized Scatter reconstruction algorithm in PET
Scattered coincidences in PET are generally taken as noise, which reduces image contrast and compromises quantification. We have developed a method, with promising results, to reconstruct activity distribution from scattered PET events instead of simply correcting for them. The implementation of this method on clinical PET scanners is however limited by the currently available detector energy resolution. With low energy resolution we lose the ability to distinguish scattered coincidences from true events based on the measured photon energy. In addition the two circular arcs used to confine the source position for a scattered event cannot be accurately defined.
This paper presents a modification to this approach which accounts for limited energy resolution. A measured event is split into a true and a scattered component each with different probabilities based on the position of the pair of photon energies in the energy spectrum. For the scattered component, we model the photon energy with a Gaussian distribution and the upper and lower energy limits can be estimated and used to define inner and outer circular arcs to confine the source position. The true and scattered components for each measured event were reconstructed using our Generalized Scatter reconstruction algorithm.
Results and Conclusion:
The results show that the contrast and noise properties were improved by 6–9% and 2–4% respectively. This demonstrates that the performance of the algorithm is less sensitive to the energy resolution and that incorporating scattered photons into reconstruction brings more benefits than simply rejecting them.