Wu Huandi, Yan Zhuangzhi, Cen Xingxing
School of Communication and Information Engineering, Shanghai University, Shanghai, 200444.
Zhongguo Yi Liao Qi Xie Za Zhi. 2020 Feb 8;44(2):95-100. doi: 10.3969/j.issn.1671-7104.2020.02.001.
Fluorescent Diffuse Optical Tomography (FDOT) is an emerging imaging method with great prospects in fields of biology and medicine. However, the current solutions to the forward problem in FDOT are time consuming, which greatly limit the application. We proposed a method for FDOT based on Lattice Boltzmann forward model on GPU to greatly improve the computational efficiency. The Lattice Boltzmann Method (LBM) was used to construct the optical transmission model. This method separated the LBM into collision, streaming and boundary processing processes on GPUs to perform the LBM efficiently, which were local computational and inefficient on CPU. The feasibility of the proposed method was verified by the numerical phantom and the physical phantom experiments. The experimental results showed that the proposed method achieved the best performance of a 118-fold speed up under the precondition of simulation accuracy, comparing to the diffusion equation implemented by Finite Element Method (FEM) on CPU. Thus, the LBM on the GPU may efficiently solve the forward problem in FDOT.
荧光漫射光学层析成像(FDOT)是一种在生物学和医学领域具有广阔前景的新兴成像方法。然而,目前FDOT中正向问题的解决方案耗时较长,这极大地限制了其应用。我们提出了一种基于GPU上的格子玻尔兹曼正向模型的FDOT方法,以大幅提高计算效率。采用格子玻尔兹曼方法(LBM)构建光传输模型。该方法将LBM在GPU上分离为碰撞、流和边界处理过程,以高效执行LBM,而这些过程在CPU上是局部计算且效率低下的。通过数值模型和物理模型实验验证了该方法的可行性。实验结果表明,与在CPU上用有限元方法(FEM)实现的扩散方程相比,该方法在模拟精度的前提下实现了最佳性能,加速比达到118倍。因此,GPU上的LBM可以有效地解决FDOT中的正向问题。