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Single particle raster image analysis of diffusion

Marco Longfils (Institutionen för matematiska vetenskaper, matematisk statistik) ; Erich Schuster ; Niklas Lorén (Institutionen för fysik, Eva Olsson Group (Chalmers) ; SuMo Biomaterials) ; Aila Särkkä (SuMo Biomaterials ; Institutionen för matematiska vetenskaper, matematisk statistik) ; Mats Rudemo (SuMo Biomaterials ; Institutionen för matematiska vetenskaper, matematisk statistik)
Journal of Microscopy (0022-2720). Vol. 266 (2016), 1, p. 3-14.
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: Bias correction , Bootstrap , Confocal laser scanning microscopy , Diffusion , Fluorescent beads , Maximum likelihood



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Denna post skapades 2017-01-19. Senast ändrad 2017-05-08.
CPL Pubid: 247387

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)
Institutionen för fysik, Eva Olsson Group (Chalmers)
SuMo Biomaterials

Ämnesområden

Materialvetenskap
Sannolikhetsteori och statistik
Annan fysik

Chalmers infrastruktur