Deconvolution in Fluorescence Lifetime imaging microscopy (FLIM)

TL;DR

This paper introduces a theoretical model for convolution in FLIM and proposes a Richardson-Lucy based deconvolution method with TV regularization to correct optical distortions in FLIM images, demonstrated on biological samples.

Contribution

The work provides the first theoretical model for convolution effects in FLIM and develops a novel deconvolution algorithm to improve image accuracy.

Findings

The deconvolution method effectively reduces distortions in FLIM images.

Experimental results show improved image quality in biological samples.

The approach enhances the interpretability of FLIM data.

Abstract

Fluorescence lifetime imaging microscopy (FLIM) is an important technique to understand the chemical micro-environment in cells and tissues since it provides additional contrast compared to conventional fluorescence imaging. When two fluorophores within a diffraction limit are excited, the resulting emission leads to non-linear spatial distortion and localization effects in intensity (magnitude) and lifetime (phase) components. To address this issue, in this work, we provide a theoretical model for convolution in FLIM to describe how the resulting behavior differs from conventional fluorescence microscopy. We then present a Richardson-Lucy (RL) based deconvolution including total variation (TV) regularization method to correct for the distortions in FLIM measurements due to optical convolution, and experimentally demonstrate this FLIM deconvolution method on a multi-photon microscopy (MPM)-FLIM images of fluorescent-labeled fixed bovine pulmonary arterial endothelial (BPAE) cells.