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ANNA-PALM / Artificial Neural Network Accelerated-PALM
Reconstructs super-resolution images from sparse single-molecule localization data and/or widefield images via a deep-learning method. ANNA-PALM process by learning the statistical properties of images from training data and then infer complete high-resolution structures. This software can generate an error map that exploits the widefield image to establish areas where images are reliable. It is available as a standalone application and as an ImageJ plug-in.
SharpViSu
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.
LAMA / LocAlization Microscopy Analyzer
Extracts quantitative information from single-molecule localization microscopy (SMLM) data. LAMA is an open source, platform-independent software tool that is relevant for biological interpretation. It processes single-molecule localizations lists and uses a selection of algorithms to return information on the nanoscale organization of proteins. It also calculates the correlation of spatial patterns of two different proteins by using a coordinate-based colocalization algorithm.
TrackNTrace
New
Allows users to locate and track single molecules. TrackNTrace intends to provide a centralized platform to: (i) identify single particles or patterns, (ii) refine their positions and extract parameters and lastly (iii) perform their tracking. This software is based on modular system, developed with the aim of easing the incorporation of external algorithms according users' needs. Besides, it can also be applied to microtubule-tip tracking or imaging with engineered point spread functions (PSFs).
EstimationTool
Assists in the estimation of the location of single molecules for a variety of different point spread function models. EstimationTool allows users to perform various estimation tasks including single molecule location estimation and resolution/distance measurements in 2D and 3D. It also offers different choices of estimation models, the ability to use either the nonlinear least squares or the maximum likelihood estimator, and supports various models for extraneous noise sources.
PALMER / PArallel Localization of Multiple Emitters via Bayesian information criterion Recommendation
Provides a super-resolution localization image analysis tool to investigate high-density single molecule images. PALMER is built on the combination of GPU parallel computation, multiple-emitter fitting and model recommendation via Bayesian Information Criterion (BIC). This software intends to avoid issues of overlapped molecules. This ImageJ module suits for fast localization microscopy.
MaLiang / Maximum Likelihood algorithm encoded on a graphics processing unit
Provides localization-based super resolution image analysis with high localization precision. MaLiang is a method based on the maximum likelihood algorithm and GPU computation. It includes a Poisson noise model that permits to describe the noise behavior of the real image frames. Three steps are successively carried out for the entire image analysis routine: (i) de-noising, (ii) sub-region extraction, and (iii) localization.
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.
NiekampEtAl2017
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.
UNLOC / UNsupervised particle LOCalization
Obsolete
Provides a list of coordinates and associated parameters for each detected particle for a posteriori quantification and image reconstruction. UNLOC is an algorithm is based on the decision theory that alternates an overestimation of the number of particles to obtain a minimal fitting residue with a general likelihood ratio test (GLRT). Moreover, it can compute the position errors based on the Cramér-Rao bound (CRB) for particles at high density per frame and without any prior on their intensity.
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