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Single particle raster image analysis of diffusion.

M Longfils¹, E Schuster², N Lorén²

¹Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden.

Journal of Microscopy

|December 6, 2016

Summary

This summary is machine-generated.

We introduce Single Particle Raster Image Analysis (SPRIA) for analyzing microscopy images. SPRIA accurately estimates particle diffusion coefficients and their standard errors, offering an alternative to standard RICS.

Keywords:

Bias correction bootstrap confocal laser scanning microscopy diffusion fluorescent beads maximum likelihood

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Area of Science:

Biophysics
Chemical Physics
Materials Science

Background:

Raster Image Correlation Spectroscopy (RICS) is a standard method for analyzing image data.
RICS analysis involves estimating the image correlation function.
A limitation of RICS is its applicability to systems with sufficient particle density.

Purpose of the Study:

To introduce a novel method, Single Particle Raster Image Analysis (SPRIA), for analyzing microscopy images.
To provide an alternative to standard RICS analysis.
To enable accurate estimation of diffusion coefficients and standard errors for individual particles.

Main Methods:

SPRIA identifies individual particles within images.
Diffusion coefficients are estimated for each particle using a maximum likelihood method.
Averaging individual estimates provides a diffusion coefficient for the entire image.

Main Results:

SPRIA provides accurate diffusion coefficient estimates for both simulated and experimental data.
The method directly yields standard error estimates.
SPRIA demonstrated potential for studying heterogeneous materials and particles with varying diffusion.

Conclusions:

SPRIA offers a complementary approach to RICS for analyzing particle dynamics.
The method is suitable for systems with low particle concentrations where individual particles can be resolved.
SPRIA facilitates accurate diffusion coefficient determination and error estimation.