Accelerating Statistical LOR Estimation for a High-Resolution PET Scanner Using FPGA Devices and a High Level Synthesis Tool

In this paper, we use an FPGA platform and a high level synthesis tool, called Impulse C, to speedup a statistical Line Of Reaction (LOR) estimation for a high-resolution Positron Emission Tomography (PET) scanner. The estimation algorithm provides a significant improvement over conventional methods, but the execution time is too long to be practical for clinic applications. Impulse C allows us to rapidly map a C program into a platform with a host processor coupled to an FPGA device. However, the generated HDLs from the original codes are very inefficient, and the execution time is even worse than the software code. We describe some optimization methods for the algorithm using Impulse C. These methods could also be applied to other applications or used to improve the high level synthesis tools. The results show that the FPGA implementation can obtain a 82× speedup over the optimized software.