Towards unsupervised fluorescence lifetime imaging using low dimensional variable projection
Zhang, Yongliang and Cuyt, Annie and Lee, Wen-shin and Lo Bianco, Giovanni and Wu, Gang and Chen, Yu and Li, David Day-Uei (2016) Towards unsupervised fluorescence lifetime imaging using low dimensional variable projection. Optics Express, 24 (23). pp. 26777-26791. ISSN 1094-4087 (https://doi.org/10.1364/OE.24.026777)
Preview |
Text.
Filename: Zhang_etal_OE2016_Towards_unsupervised_fluorescence_lifetime.pdf
Final Published Version License: Download (8MB)| Preview |
Abstract
Analyzing large fluorescence lifetime imaging (FLIM) data is becoming overwhelming: the latest FLIM systems easily produce massive amounts of data, making the efficient analysis more challenging than ever. In this paper we propose the combination of a custom-fit variable projection method, with a Laguerre expansion based deconvolution, to analyze bi-exponential data obtained from time-domain FLIM systems. Unlike nonlinear least squares methods, which require a suitable initial guess from an experienced researcher, the new method is free from manual interventions and hence can support automated analysis. Monte Carlo simulations are carried out on synthesized FLIM data to demonstrate the performance compared to other approaches. The performance is also illustrated on real-life FLIM data obtained from the study of autofluorescence of daisy pollen and the endocytosis of gold nanorods (GNRs) in living cells. In the latter, the fluorescence lifetimes of the GNRs are much shorter than the full width at half maximum of the instrument response function. Overall, our proposed method contains simple steps and shows great promise in realising automated FLIM analysis of large datasets.
ORCID iDs
Zhang, Yongliang, Cuyt, Annie, Lee, Wen-shin, Lo Bianco, Giovanni, Wu, Gang, Chen, Yu and Li, David Day-Uei ORCID: https://orcid.org/0000-0002-6401-4263;-
-
Item type: Article ID code: 58215 Dates: DateEvent14 November 2016Published10 November 2016Published Online19 October 2016AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) > Bioengineering
Science > Physics > Optics. Light
Science > MathematicsDepartment: Faculty of Science > Physics
Technology and Innovation Centre > Bionanotechnology
Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical SciencesDepositing user: Pure Administrator Date deposited: 24 Oct 2016 10:21 Last modified: 11 Nov 2024 11:32 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/58215