Medical imaging process accelerated in FPGA 82X faster than software

Zhongho Chen, Alvin W.Y. Su, Ming-Ting Sun, and Scott Hauck
EETimes (6/21/2011 3:42 PM EDT)

Medical imaging tasks can require high-performance signal processing to convert sensor data into imagery to help with medical diagnostics.  FPGAs are a compelling platform for these systems, since they can perform heavily pipelined operations customized to the exact needs of a given computation.  In previous work we have benchmarked a CT scanner back-projection algorithm.  In this article we focus on an FPGA platform and a high level synthesis tool called Impulse C to speed up 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 and an FPGA coprocessor. In this article, we describe some successful optimization methods for the algorithm using Impulse C. The results show that the FPGA implementation can obtain an 82x speedup over the optimized software.

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