Abstract

Interferometric scattering (iSCAT) microscopy has been demonstrated as a powerful tool for tracking single nanoparticles at ultrahigh spatial and temporal resolutions. The unmatched performance of iSCAT single-particle tracking (SPT) relies on the fact that the scattering signal is steady and can be linearly increased under strong illumination, circumventing the problems of photobleaching and saturation of fluorescence-based approaches. However, the scattering-based imaging is complicated by the presence of nonspecific scattering background, e.g. in the complex samples of biological cells. To distinguish the signal of interest from the nonspecific scattering background, metallic nanoparticles are often used as the efficient scattering probes. In many applications, reduction of the particle size is favorable because the loading of particle may introduce labeling artifacts. To work with smaller particles of weaker signal, suppression of the heterogeneous background is necessary. In this work, we start with the characterization of dynamic iSCAT signal of living cells by calculating its spatial and temporal Fourier spectra. To reduce the influence of cell background to SPT, a common strategy of background estimation and correction by temporal average filtering is considered. The effect of residual cell background to SPT is evaluated systematically with simulated image data of various signal-to-background ratios. This work benchmarks the localization errors caused by the cell background in SPT, providing a guideline for the interpretation of single-particle diffusion data of iSCAT microscopy.

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