3‐D PSF fitting for fluorescence microscopy: implementation and localization application

Summary Localization microscopy relies on computationally efficient Gaussian approximations of the point spread function for the calculation of fluorophore positions. Theoretical predictions show that under specific experimental conditions, localization accuracy is significantly improved when the lo...

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Bibliographic Details
Published in:Journal of microscopy (Oxford) 2013-01, Vol.249 (1), p.13-25
Main Authors: KIRSHNER, H., AGUET, F., SAGE, D., UNSER, M.
Format: Article
Language:English
Subjects:
3‐D PSF models
Algorithms
Computational Biology - methods
Computational efficiency
Fittings
Fluorescent Dyes - chemistry
Imaging, Three-Dimensional - methods
Least-Squares Analysis
Localization
Mathematical models
Microscopy
Microscopy, Fluorescence - methods
Photons
Point spread functions
Poisson Distribution
Position (location)
Refractometry
Reproducibility of Results
Sensitivity and Specificity
Single molecule localization microscopy
Studies
Three dimensional
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Summary:Summary Localization microscopy relies on computationally efficient Gaussian approximations of the point spread function for the calculation of fluorophore positions. Theoretical predictions show that under specific experimental conditions, localization accuracy is significantly improved when the localization is performed using a more realistic model. Here, we show how this can be achieved by considering three‐dimensional (3‐D) point spread function models for the wide field microscope. We introduce a least‐squares point spread function fitting framework that utilizes the Gibson and Lanni model and propose a computationally efficient way for evaluating its derivative functions. We demonstrate the usefulness of the proposed approach with algorithms for particle localization and defocus estimation, both implemented as plugins for ImageJ.
ISSN:0022-2720
1365-2818
DOI:10.1111/j.1365-2818.2012.03675.x