Volume Reconstruction for Light Field Microscopy

Abstract

Light Field Microscopy (LFM) is a 3D imaging technique that captures volumetric information in a single snapshot. It is appealing in microscopy because of its simple implementation and the peculiarity that it is much faster than methods involving scanning. However, volume reconstruction for LFM suffers from low lateral resolution, high computational cost, and reconstruction artifacts near the native object plane. In this work, we make two contributions. First, we propose a simplification of the forward model based on a novel discretization approach that allows us to accelerate the computation without drastically increasing memory consumption. Second, we experimentally show that by including regularization priors and an appropriate initialization strategy, it is possible to remove the artifacts near the native object plane. The algorithm we use for this is ADMM. Finally, the combination of the two techniques leads to a method that outperforms classic volume reconstruction approaches (variants of Richardson-Lucy) in terms of average computational time and image quality (PSNR).