ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging

Area of Science:

• Microscopy
• Biophysics
• Image Analysis

Background:

• Single-molecule localization microscopy (SMLM) generates high-resolution biological data.
• Analyzing SMLM data requires specialized software for accurate processing and visualization.

Purpose of the Study:

• To introduce ThunderSTORM, an open-source ImageJ plugin for SMLM data analysis.
• To provide a modular and interactive platform for automated processing, analysis, and visualization of SMLM datasets.
• To offer tools for data simulation and performance evaluation of localization algorithms.

Main Methods:

• Development of an interactive and modular ImageJ plugin named ThunderSTORM.
• Implementation of a comprehensive suite of processing and post-processing methods for SMLM data.
• Integration of tools for generating simulated SMLM data and performing quantitative performance evaluations using Monte Carlo simulations.

Main Results:

• ThunderSTORM enables automated processing, analysis, and visualization of SMLM data.
• The plugin allows users to customize analysis workflows for diverse datasets.
• It facilitates the creation of simulated data for algorithm benchmarking.

Conclusions:

• ThunderSTORM is a versatile and accessible tool for the SMLM community.
• It empowers researchers to efficiently analyze complex SMLM data and evaluate localization algorithm performance.
• The open-source nature and comprehensive features of ThunderSTORM promote reproducible research in super-resolution microscopy.