Fourier Domain Optical Coherence Tomography is an emerging biomedical imaging technology that provides ultra high resolution and a fast imaging speed. The complexity of the FD-OCT algorithm demands high processing power from the underlying platform. However, the scaling of faster data acquisition rates and 3D imaging on real time FD-OCT systems is quickly outpacing the performance growth of General Purpose Processors. Our research investigates the scalability of two potential platforms for accelerating FD-OCT — GPGPUs and FPGAs. We implemented a FD-OCT system using a GPGPU as co-processor with 6.9x speed up. We also created a hardware processing engine using FPGAs, delivering over 2x the throughput rate over GPGPU with 1024- point FFT. Our analysis on the performance and scalability for both platforms shows that, while GPGPUs offer an easy and low cost solution for accelerating FD-OCT, FPGAs are more likely to match the long term demands for real-time, 3D FD-OCT.
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