Pet image reconstruction: GPU-accelerated particle filter framework

In this paper, we explore the usage of graphics processing units (GPU)-accelerated particle filter strategies for the estimation of activity map in tomographic PET imaging. The proposed framework formulates the physiological model of the imaging tissues through state space evolution equations and the photon counting statistics through observation equations, and then reconstruction is performed using particle filter estimation. For fast reconstruction, the calculations are implemented using highly-parallel GPU. Experiments show that the image quality is improved through particle filter. Furthermore, thanks to the computing power of graphics hardware, reconstruction times are practical for clinical applications.