Hardware Architecture Design for Iterative Reconstruction Algorithms Toward Palm-Size Photoacoustic Tomography

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Abstract
Photoacoustic (PA) imaging technology integrates the deep penetration depth of ultrasound imaging with the high resolution of optical imaging, demonstrating significant potential in biomedical applications. Many preclinical studies and clinical applications urgently require a portable, high-quality, low-cost, and fast imaging system. Thus, translating advanced image reconstruction algorithms into hardware implementations is highly desired. However, existing iterative PA image reconstructions, although exhibit higher accuracy than the delay-and-sum algorithm, suffer from high computational cost. In this paper, we introduce a novel model-based hardware architecture for palm-size PA tomography (palm-PAT), aiming at enhancing both the speed and performance of image reconstruction at a much lower system cost. To achieve this, we propose an innovative data reuse method that significantly reduces the consumption of hardware storage resources, achieving a reduction of approximately 75% in hardware storage requirements. We conducted experiments utilizing the FPGA implementation of the algorithm, using phantom, human finger data in vivo and ex vivo breast tumor data to verify the feasibility of the proposed method. The results demonstrate that our proposed architecture can substantially reduce system cost while maintaining high imaging performance. The novel hardware architecture design of the model-based algorithm achieves a speedup of up to approximately 270 times compared to the CPU, while the corresponding energy efficiency ratio is improved by more than 2700 times.
Funding Information
  • National Natural Science Foundation of China (61805139)
  • Shanghai Clinical Research and Trial Center (2022A0305-418- 02)
  • Double First-Class Initiative Fund of ShanghaiTech University (2022X0203-904-04)

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