title: Robust Bayesian Fluorescence Lifetime Estimation, Decay Model Selection and Instrument Response Determination for Low-Intensity FLIM Imaging.
abstract: We present novel Bayesian methods for the analysis of exponential decay data that exploit the evidence carried by every detected decay event and enables robust extension to advanced processing. Our algorithms are presented in the context of fluorescence lifetime imaging microscopy (FLIM) and particular attention has been paid to model the time-domain system (based on time-correlated single photon counting) with unprecedented accuracy. We present estimates of decay parameters for mono- and bi-exponential systems, offering up to a factor of two improvement in accuracy compared to previous popular techniques. Results of the analysis of synthetic and experimental data are presented, and areas where the superior precision of our techniques can be exploited in Förster Resonance Energy Transfer (FRET) experiments are described. Furthermore, we demonstrate two advanced processing methods: decay model selection to choose between differing models such as mono- and bi-exponential, and the simultaneous estimation of instrument and decay parameters.
authors.affiliation: Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom.
authors.forename: Mark I
authors.initials: MI
authors.lastname: Rowley
authors.affiliation: Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom.
authors.forename: Anthonius C C
authors.initials: AC
authors.lastname: Coolen
authors.affiliation: Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
authors.forename: Borivoj
authors.initials: B
authors.lastname: Vojnovic
authors.affiliation: Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom.|Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
authors.forename: Paul R
authors.initials: PR
authors.lastname: Barber
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D045744:Cell Line, Tumor; D005453:Fluorescence; D031541:Fluorescence Resonance Energy Transfer; D006801:Humans; D016018:Least-Squares Analysis; D016013:Likelihood Functions; D008856:Microscopy, Fluorescence; D008962:Models, Theoretical; D009369:Neoplasms / Q000473:pathology*