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Performance and scalability of Fourier domain optical coherence tomography acceleration using graphics processing
Jian Li1, Pavel Bloch, Jing Xu
1School of Engineering Sciences, Simon Fraser University, V5A 1S6 Burnaby, BC, Canada. jla193@sfu.ca
Applied Optics
|May 3, 2011
Summary
Graphics processing units (GPUs) accelerate Fourier domain optical coherence tomography (FD-OCT) imaging. However, FD-OCT performance is limited by GPU memory transfer times, not processing speed, impacting real-time biomedical applications.
Area of Science:
- Biomedical Imaging
- Optical Coherence Tomography
- Computational Imaging
Background:
- Fourier domain optical coherence tomography (FD-OCT) offers superior performance over time domain OCT (TD-OCT) for in vivo biomedical imaging.
- Real-time FD-OCT requires computationally intensive signal processing, necessitating powerful computing platforms.
- Graphics processing units (GPUs) are utilized as coprocessors to accelerate FD-OCT, exploiting their parallel processing capabilities.
Purpose of the Study:
- To implement and evaluate a complete FD-OCT accelerator on a consumer-grade GPU/CPU platform.
- To identify the performance bottlenecks in GPU-accelerated FD-OCT systems.
- To assess the suitability of current GPU architectures for future FD-OCT data rate requirements.
Main Methods:
- Implementation of a spectrometer-based data acquisition system with a dual-arm interferometer.
- Utilization of numerical dispersion compensation for retinal imaging applications.
- Development of a complete FD-OCT accelerator leveraging GPU parallel processing and a consumer-grade GPU/CPU platform.
Main Results:
- The maximum line rate of the implemented FD-OCT system is constrained by memory transfer times between the GPU and CPU, rather than computational processing time.
- The GPU platform's memory architecture dictates the overall system performance, highlighting a critical bottleneck for real-time applications.
- Analysis of performance trends indicates potential limitations for meeting future FD-OCT data rate demands with current GPU architectures.
Conclusions:
- GPU-based accelerators show promise for FD-OCT but are currently limited by memory transfer speeds.
- Optimizing data transfer between host and GPU processors is crucial for achieving higher line rates in real-time FD-OCT.
- Future advancements in GPU memory technology and architecture are needed to fully realize the potential of real-time FD-OCT.
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