Analysis of Super-resolution Single Molecule Localization Microscopy Data: a tutorial

TL;DR

This paper reviews recent advances in data processing and post-processing techniques for super-resolution single molecule localization microscopy, highlighting methods that overcome diffraction limits to achieve high-resolution biological imaging.

Contribution

It provides a comprehensive tutorial on the latest SMLM data analysis methods, emphasizing improvements in localization accuracy and image reconstruction.

Findings

Enhanced localization precision techniques

Improved image reconstruction algorithms

Quantitative analysis of biological structures

Abstract

The diffraction of light imposes a fundamental limit on the resolution of light microscopes. This limit can be circumvented by creating and exploiting independent behaviors of the sample at length scales below the diffraction limit. In super-resolution single molecule localization microscopy (SMLM), the independence arises from individual fluorescent labels stochastically switching between dark and fluorescent states, which in turn allows the pinpointing of fluorophores post experimentally using a sequence of acquired sparse image frames. Finally, the resulting list of fluorophore coordinates is utilized to produce high resolution images or to gain quantitative insight into the underlying biological structures. Therefore, image processing and post-processing are essential stages of SMLM. Here, we review the latest progress on SMLM data processing and post-processing.