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An interactive open-source software with a graphical user interface, which allows performing processing steps for localization data in an integrated manner. This includes common features and new tools such as correction of chromatic aberrations, drift correction based on iterative cross-correlation calculations, selection of localization events, reconstruction of 2D and 3D datasets in different representations, estimation of resolution by Fourier ring correlation, clustering analysis based on Voronoi diagrams and Ripley’s functions. SharpViSu is optimized to work with eventlist tables exported from most popular localization software. The functionality of SharpViSu is extendable via plugins, such as ClusterViSu for comprehensive cluster analysis of localization microscopy data. It includes tools such as calculations of Voronoi and Ripley statistics with Monte-Carlo simulations, different modes of reconstruction (e.g. based on Gaussian blur or Ripley’s functions) and segmentation of density maps, retrieval of geometrical properties of detected clusters, segmentation based on Voronoi tessellation.

FOCAL / Fast Optimized Cluster Algorithm for Localizations

A grid-based clustering algorithm FOCAL, which explicitly accounts for several dominant artifacts arising in SMLM image reconstructions. FOCAL is fast and efficient, scaling like O(n), and only has one set parameter. We assess DBSCAN and FOCAL on experimental dSTORM data of clusters of eukaryotic RNAP II and PALM data of the bacterial protein H-NS, then provide a detailed comparison via simulation. FOCAL performs comparable and often superior to DBSCAN while yielding a significantly faster analysis. Additionally, FOCAL provides a novel method for filtering out of focus clusters from complex SMLM images.


Measures distances on the length scale of most macromolecules by using two-color fluorescence microscopy procedures. The software is a plug-in that can be added the µManager software. It can be used for three different tasks: (i) measuring distances and investigating conformational heterogeneity of biological macromolecules; (ii) featuring dynamic changes in protein conformation and; (iii) studying biophysical properties of motor proteins such as dyneins, kinesins, and myosins.

GraspJ / GPU-Run Analysis for STORM and PALM

An open source, real-time data analysis and rendering tool for super-resolution imaging techniques that are based on single molecule detection and localization (e.g. stochastic optical reconstruction microscopy - STORM and photoactivation localization microscopy – PALM). GraspJ is an ImageJ plug-in with a convenient user interface, that allows high accuracy localization of single molecules as well as processing and rendering of high resolution images in real-time. GraspJ includes several features such as drift correction, multi-color, 3D analysis/rendering, and is compatible with a large range of data acquisition software. In addition, it allows easy interfacing with other image processing tools available with ImageJ.