Performance evaluation of adaptive meshing algorithms for fluorescence diffuse optical tomography using experimental data

Abstract

Fluorescence diffuse optical tomography (FDOT) is a computationally demanding imaging problem. The discretizations of FDOT forward and inverse problems pose a trade-off between the accuracy and the computational efficiency of the image reconstruction. To address this trade-off, we analyzed the effect of discretization on the accuracy of FDOT imaging and proposed novel adaptive meshing algorithms for FDOT in a series of studies. In this Letter, we apply these new adaptive meshing algorithms to FDOT imaging using real data from a phantom experiment to demonstrate the practical advantages of our algorithms in FDOT image reconstruction.