A fast 3D image reconstruction method based on Monte-Carlo simulation for laminar optical tomography

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 takes too much computation time. Based on the scheme of trajectory translation and target voxel regression (TT&TVR) proposed by our group, this paper develops a fast 3D image reconstruction algorithm. The algorithm is applied to the absorption reconstruction of the layered inhomogeneous media. Results demonstrate that the reconstructing time is less than 15min with the X-Y-Z section of the sample subdivided into 50 × 50 × 10 voxels, and the target size and quantitativeness ratio can be obtained in a satisfying accuracy.