Title: A Bayesian Approach for Extracting Fluorescence Lifetimes from Sparse Data Sets and Its Significance for Imaging Experiments

Abstract

The measurement of fluorescence lifetimes, especially in small sample volumes, presents the dual challenge of probing a small number of fluorophores and fitting the concomitant sparse data set to the appropriate excited-state decay function. A common method of analysis, such as the maximum likelihood (ML) technique, assumes a uniform probability distribution of the parameters describing the fluorescence decay function. An improvement is thus suggested by implementing a suitable nonuniform distribution, as is provided by a Bayesian framework, where the distribution of parameters is obtained from both their prior knowledge and the evidence-based likelihood of an event for a given set of parameters. We have also considered the Dirichlet prior distribution, whose mathematical form enables analytical solutions of the fitting parameters to be rapidly obtained. If Gaussian and exponential prior distributions are judiciously chosen, they reproduce the experimental target lifetime to within 20% with as few as 20 total photon counts for the data set, as does the Dirichlet prior distribution. But because of the analytical solutions afforded by the Dirichlet prior distribution, it is proposed to employ a Dirichlet prior to search parameter space rapidly to provide, if necessary, appropriate parameters for subsequent employment of a Gaussian or exponential priormore » distribution« less

Authors:

Santra, Kalyan  ^[1];

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Smith, Emily A. ^[1]; Song, Xueyu ^[1]; Petrich, Jacob W. ^[1]

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+ Show Author Affiliations

1. Ames Lab. and Iowa State Univ., Ames, IA (United States). Dept. of Chemistry

Publication Date:

Sat Dec 22 00:00:00 EST 2018

Research Org.:

Ames Laboratory (AMES), Ames, IA (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER)

OSTI Identifier:

1492061

Alternate Identifier(s):

OSTI ID: 1488690

Report Number(s):

IS-J-9839
Journal ID: ISSN 0031-8655

Grant/Contract Number:  

AC02-07CH11358; AC02‐07CH11358

Resource Type:

Accepted Manuscript

Journal Name:

Photochemistry and Photobiology

Additional Journal Information:

Journal Volume: 95; Journal Issue: 3; Journal ID: ISSN 0031-8655

Publisher:

The American Society of Photobiology

Country of Publication:

United States

Language:

English

Subject:

97 MATHEMATICS AND COMPUTING