An efficient lattice Boltzmann method for fluorescent diffuse optical tomography on GPUs

Abstract

Fluorescent diffuse optical tomography (FDOT) is an emerging imaging modality, with great prospects in areas such as biology and medicine. However, current FDOT encounters difficulty in simulating photon propagation in biological tissue, i.e., the forward problem, which limits its further application in biomedical research. This paper presents a lattice Boltzmann method (LBM) on the GPU to greatly improve the computational efficiency in the forward problem realization. This method separated the LBM simulating the propagation of photon in tissues into collision, streaming and boundary processing processes on GPUs, which are local computational processes and inefficient on CPU, so that we can perform the LBM efficiently. Both the numerical phantom and the physical phantom experiments were carried out to evaluate the performance of the proposed method. The experimental results showed that the proposed method achieved the best performance of 2471 mega lattice-updates per second (MLUPS) and a 118-fold speedup under the precondition of simulation accuracy, compared to the diffusion equation implemented by finite element method (FEM) on CPU. Thus, the LBM on the GPU has the potential for efficiently solving the forward problem in FDOT.