A lateral resolution metric for static single molecule localization microscopy images from time-resolved pair correlation functions

TL;DR

This paper introduces a new resolution metric for static SMLM images based on time-resolved pair correlation functions, providing an objective measure of effective resolution considering drift and correction effects.

Contribution

The authors present a simple, objective method using pair autocorrelation functions in space and time to evaluate the resolution of static SMLM images, accounting for drift effects.

Findings

Experimental images have broader PSFs than expected from localization precision.

The metric complements Fourier Ring Correlation by considering spatial sampling.

Demonstrated on simulated and biological samples.

Abstract

Single molecule localization microscopy (SMLM) permits the visualization of cellular structures an order of magnitude smaller than the diffraction limit of visible light, and an accurate, objective evaluation of the resolution of an SMLM dataset is an essential aspect of the image processing and analysis pipeline. Here we present a simple method that uses the pair autocorrelation function evaluated both in space and time to measure the time-interval dependent point-spread function of SMLM images of static samples. Using this approach, we demonstrate that experimentally obtained images typically have effective point spread functions that are broader than expected from the localization precision alone, due to additional uncertainty arising from drift and drift correction algorithms. This resolution metric reports on how precisely one can measure pairwise distances between labeled objects and is complementary to the commonly used Fourier Ring Correlation metric that also considers spatial sampling. The method is demonstrated on simulated localizations, DNA origami rulers, and cellular structures labelled by dye-conjugated antibodies or fluorescent fusion proteins.