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Single particle raster image analysis of diffusion
Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
RISE - Research Institutes of Sweden, Bioscience and Materials, Agrifood and Bioscience.
RISE - Research Institutes of Sweden, Bioscience and Materials, Agrifood and Bioscience.
Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.
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2017 (English)In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 266, no 1, 3-14 p.Article in journal (Refereed) Published
Abstract [en]

As a complement to the standard RICS method of analysing Raster Image Correlation Spectroscopy images with estimation of the image correlation function, we introduce the method SPRIA, Single Particle Raster Image Analysis. Here, we start by identifying individual particles and estimate the diffusion coefficient for each particle by a maximum likelihood method. Averaging over the particles gives a diffusion coefficient estimate for the whole image. In examples both with simulated and experimental data, we show that the new method gives accurate estimates. It also gives directly standard error estimates. The method should be possible to extend to study heterogeneous materials and systems of particles with varying diffusion coefficient, as demonstrated in a simple simulation example. A requirement for applying the SPRIA method is that the particle concentration is low enough so that we can identify the individual particles. We also describe a bootstrap method for estimating the standard error of standard RICS.

Place, publisher, year, edition, pages
2017. Vol. 266, no 1, 3-14 p.
Keyword [en]
Bias correction, bootstrap, confocal laser scanning microscopy, diffusion, fluorescent beads, maximum likelihood
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:ri:diva-29181DOI: 10.1111/jmi.12511Scopus ID: 2-s2.0-85006356767OAI: oai:DiVA.org:ri-29181DiVA: diva2:1086589
Available from: 2017-04-03 Created: 2017-04-03 Last updated: 2017-04-03Bibliographically approved

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