Image reconstruction method for laminar optical tomography with only a single Monte-Carlo simulation

Abstract

Laminar optical tomography (LOT) is a new mesoscopic functional optical imaging technique. Currently, the forward problem of LOT image reconstruction is generally solved on the basis of Monte-Carlo (MC) methods. However, considering the nonlinear nature of the image reconstruction in LOT with the increasing number of source positions, methods based on MC take too much computation time. This letter develops a fast image reconstruction algorithm based on perturbation MC (pMC) for reconstructing the absorption or scattering image of a slab medium, which is suitable for LOT or other functional optical tomography system with narrow source-detector separation and dense sampling. To calculate the pMC parameters, i.e., the path length passed by a photon and the collision numbers experienced in each voxel with only one baseline MC simulation, we propose a scheme named as the trajectory translation and target voxel regression (TT&TVR) based on the reciprocity principle. To further speed up the image reconstruction procedure, the weighted average of the pMC parameters for all survival photons is adopted and the region of interest (ROI) is extracted from the raw data to save as the prior information of the image reconstruction. The method is applied to the absorption reconstruction of the layered inhomogeneous media. Results demonstrate that the reconstructing time is less than 20 s with the X-Y section of the sample subdivided into 50 \times 50 voxels, and the target size quantitativeness ratio can be obtained in a satisfying accuracy in the source-detector separations of 0.4 and 1.25 mm, respectively.