High-speed imaging capability is essential for photoacoustic computed tomography (PACT) to monitor biological dynamics. The filtered back-projection (FBP) algorithm is widely-used in PACT for image reconstruction owing to its high computational efficiency. To achieve high-speed imaging, several acceleration strategies based on the graphics processing units (GPUs) have been proposed to further increase the computational efficiency of the FBP algorithm. However, there are few acceleration strategies reported based on the multi-core central processing units (CPUs). Considering the fact that multi-core CPUs are much more accessible than high-performance GPUs, here we report a multi-core CPU-based framework for enhancing the computational efficiency of the FBP algorithm. In this framework, the highly-parallel back-projection part of the FBP algorithm is programed with C++ and implemented in parallel with multi-core CPUs. In addition, the pre-calculation strategy is applied in this framework to avoid unnecessary repetitive computations. The results show that implementing the back-projection part in parallel with C++ can reduce the image reconstruction time by a factor of 2.4 compared with the conventional implementation in which the FBP algorithm is fully programed with MATLAB and executed in parallel with parfor. By applying the pre-calculation, the image reconstruction time is further reduced by a factor of 2.2. Overall, the proposed framework increases the computational efficiency of the FBP algorithm by a factor of 5.5 and only takes 0.04 seconds to reconstruct an image with 512 × 512 pixels. This work is expected to promote the development of high-performance PACT systems that feature high imaging speed without GPUs.
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