Three-dimensional (3D) image reconstruction involves the computations of an extensive amount of data that leads to tremendous processing time. Therefore, optimization is crucially needed to improve the performance and efficiency. With the widespread use of graphics processing units (GPU), parallel computing is transforming this arduous reconstruction process for numerous imaging modalities, and photoacoustic computed tomography (PACT) is not an exception. Existing works have investigated GPU-based optimization on photoacoustic microscopy (PAM) and PACT reconstruction using compute unified device architecture (CUDA) on either C++ or MATLAB only. However, our study is the first that uses cross-platform GPU computation. It maintains the simplicity of MATLAB, while improves the speed through CUDA/C++ − based MATLAB converted functions called MEXCUDA. Compared to a purely MATLAB with GPU approach, our cross-platform method improves the speed five times. Because MATLAB is widely used in PAM and PACT, this study will open up new avenues for photoacoustic image reconstruction and relevant real-time imaging applications.

中文翻译：

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使用跨平台并行计算优化光声图像重建

三维（3D）图像重建涉及大量数据的计算，这导致了巨大的处理时间。因此，迫切需要优化以提高性能和效率。随着图形处理单元（GPU）的广泛使用，并行计算正在将这种艰巨的重建过程转变为多种成像方式，并且光声计算机断层扫描（PACT）也不例外。现有工作已经研究了仅在C ++或MATLAB上使用计算统一设备架构（CUDA）在光声显微镜（PAM）和PACT重建上基于GPU的优化。但是，我们的研究是第一个使用跨平台GPU计算的研究。它保持了MATLAB的简单性，同时通过基于CUDA / C ++的MATLAB转换函数MEXCUDA提高了速度。与纯MATLAB和GPU方法相比，我们的跨平台方法将速度提高了五倍。由于MATLAB已广泛用于PAM和PACT中，因此本研究将为光声图像重建和相关的实时成像应用开辟新的途径。