互相关计算方法的性能对超声弹性成像运动的计算效率起着决定性的作用。在串行计算环境下, 基于和表的快速互相关算法在维持计算精度的同时可以获得更快的计算效率。然而, 在并行计算环境下, 尤其是 GPU平台上, 基于和表的快速互相关算法的实现以及性能还没有相关的报道。在本研究中, 以二维超声弹性成像的运动追踪应用为目标, 基于和表的快速互相关算法(ST-NCC)在 GPU平台上得以实现, 并且从计算效率及计算精度和传统的互相关算法进行了详细比较。初步结果显示, 虽然基于和表的快速互相关算法 (ST-NCC)在串行计算环境下获得了较好的计算效率, 但是在 GPU环境下, 两种方法的计算效率没有较大的差距。

The calculation of correlation is critically important for ultrasound strain elastography. The sum-table based method for the calculation of the normalized correlation coefficient (ST-NCC) can greatly improve computational efficiency under an environment of serial computing. Its implementation and performance are yet to be investigated when given a parallel computing platform, particularly, under a GPU environment. In this study, the published ST-NCC method was implemented into GPU and its performance was evaluated for speckle tracking. Particularly, the performance of the ST-NCC method was compared to the classic method of computing NCC using simulated ultrasound data. Our preliminary results indicated that, under the GPU platform, the implemented ST-NCC method did not further improve the computational efficiency, as compared to the classic NCC method implemented into the same GPU platform.