Analysis of Fluorescence Lifetime Imaging Microscopy (FLIM) Data

Abstract

A novel Fluorescence Lifetime Imaging Microscopy (FLIM) deconvolution method based on the linear expansion of fluorescence decays on a set of orthonormal Laguerre functions was recently proposed. The Laguerre deconvolution method applies linear least-square estimation to estimate the expansion coefficients of all pixel decays simultaneously, performing at least two orders of magnitude faster than the other algorithms. In the original Laguerre FLIM deconvolution implementation, however, the Laguerre parameter α is selected using a heuristic approach, making it unsuitable for online applications. In this study, we present a fully automated implementation of the Laguerre FLIM deconvolution, whereby the Laguerre parameter α is treated as a free parameter within a nonlinear least-squares optimization scheme. The performance of this method has been successfully validated on simulated data, and experimental FLIM images of standard fluorescent dyes and endogenous tissue fluorescence. The main advantage of the proposed method is that it does not require any user intervention for tuning up the deconvolution process. Thus, we believe this method will facilitate the translation of FLIM to online applications, including real-time clinical diagnosis.