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Fisher information theory for parameter estimation in single molecule microscopy: Tutorial

Fisher information theory for parameter estimation in single molecule microscopy: Tutorial
Fisher information theory for parameter estimation in single molecule microscopy: Tutorial

Estimation of a parameter of interest from image data represents a task that is commonly carried out in single molecule microscopy data analysis. The determination of the positional coordinates of a molecule from its image, for example, forms the basis of standard applications such as single molecule tracking and localization-based super-resolution image reconstruction. Assuming that the estimator used recovers, on average, the true value of the parameter, its accuracy, or standard deviation, is then at best equal to the square root of the Cramér-Rao lower bound. The Cramér-Rao lower bound can therefore be used as a benchmark in the evaluation of the accuracy of an estimator. Additionally, as its value can be computed and assessed for different experimental settings, it is useful as an experimental design tool. This tutorial demonstrates a mathematical framework that has been specifically developed to calculate the Cramér-Rao lower bound for estimation problems in single molecule microscopy and, more broadly, fluorescence microscopy. The material includes a presentation of the photon detection process that underlies all image data, various image data models that describe images acquired with different detector types, and Fisher information expressions that are necessary for the calculation of the lower bound. Throughout the tutorial, examples involving concrete estimation problems are used to illustrate the effects of various factors on the accuracy of parameter estimation and, more generally, to demonstrate the flexibility of the mathematical framework.

1084-7529
B36-B57
Chao, Jerry
550e20b0-8365-42e3-a6fc-1048eb8c2e47
Ward, E. Sally
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
Chao, Jerry
550e20b0-8365-42e3-a6fc-1048eb8c2e47
Ward, E. Sally
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36

Chao, Jerry, Ward, E. Sally and Ober, Raimund J. (2016) Fisher information theory for parameter estimation in single molecule microscopy: Tutorial. Journal of the Optical Society of America A, 33 (7), B36-B57. (doi:10.1364/JOSAA.33.000B36).

Record type: Article

Abstract

Estimation of a parameter of interest from image data represents a task that is commonly carried out in single molecule microscopy data analysis. The determination of the positional coordinates of a molecule from its image, for example, forms the basis of standard applications such as single molecule tracking and localization-based super-resolution image reconstruction. Assuming that the estimator used recovers, on average, the true value of the parameter, its accuracy, or standard deviation, is then at best equal to the square root of the Cramér-Rao lower bound. The Cramér-Rao lower bound can therefore be used as a benchmark in the evaluation of the accuracy of an estimator. Additionally, as its value can be computed and assessed for different experimental settings, it is useful as an experimental design tool. This tutorial demonstrates a mathematical framework that has been specifically developed to calculate the Cramér-Rao lower bound for estimation problems in single molecule microscopy and, more broadly, fluorescence microscopy. The material includes a presentation of the photon detection process that underlies all image data, various image data models that describe images acquired with different detector types, and Fisher information expressions that are necessary for the calculation of the lower bound. Throughout the tutorial, examples involving concrete estimation problems are used to illustrate the effects of various factors on the accuracy of parameter estimation and, more generally, to demonstrate the flexibility of the mathematical framework.

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e-pub ahead of print date: 22 June 2016
Published date: 1 July 2016

Identifiers

Local EPrints ID: 423670
URI: https://eprints.soton.ac.uk/id/eprint/423670
ISSN: 1084-7529
PURE UUID: 3600d0cc-2422-408b-a53a-e23465416276
ORCID for E. Sally Ward: ORCID iD orcid.org/0000-0003-3232-7238
ORCID for Raimund J. Ober: ORCID iD orcid.org/0000-0002-1290-7430

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Date deposited: 27 Sep 2018 16:30
Last modified: 14 Mar 2019 01:21

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Contributors

Author: Jerry Chao
Author: E. Sally Ward ORCID iD
Author: Raimund J. Ober ORCID iD

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