Evaluation of reconstruction algorithms for triple-head coincidence imaging by hot sphere detectability

Simulations and measurements of triple head PET acquisitions of a hot sphere phantom were performed to evaluate the performance of two different reconstruction algorithms (projection based ML-EM and listmode ML-EM)for triple head gamma camera coincidence systems. A geometric simulator assuming a detector with 100 percent detection efficiency and only detection of trues was used. The resolution was equal to the camera system. The measurements were performed with a triple headed gamma camera. Simulated and measured data were stored in listmode format, which allowed the flexibility for different reconstruction algorithms. As a measure for the performance the hot spot detectability was taken because tumor imaging is the most important clinical application for gamma camera coincidence systems. The detectability was evaluated by calculating the recovered contrast and the contrast-to-noise ratio. Results show a slightly improved contrast but a clearly higher contrast-to-noise ratio for list mode reconstruction.