Single molecule localization microscopy

Direct stochastic optical reconstruction microscopy
Photoactivated Localization Microscopy
Fluorescence Photoactivation Localization Microscopy
Ground State Depletion Individual Molecule Return
Stochastic optical reconstruction microscopy

Software for computing single molecule localization accuracies and resolution measures

The FandPLimitTool is a GUI based software module that allows users to calculate the limits to the accuracy with which parameters can be estimated from single molecule imaging data. The software supports calculation of limits for the 2D/3D location estimation problem and the 2D/3D distance-estimation/resolution problem. The location estimation problem is concerned with the task of determining the position of a single molecule and the distance-estimation/resolution problem is concerned with the task of determining the distance of separation between two single molecules. The user can calculate limits for a variety of imaging scenarios.

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NanoJ-SQUIRREL (Super-resolution Quantitative Image Rating and Reporting of Error Locations) is a software package designed for assessing and mapping errors and artefacts within super-resolution images. This is achieved through quantitative comparison with a reference image of the same structure (typically a widefield, TIRF or confocal image). SQUIRREL produces quantitative maps of image quality and resolution as well as global image quality metrics.

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This script includes a rough feature detection and then fine 2D Gaussian algorithm to fit Gaussians within detected regions. This macro is unique because the ImageJ/Fiji curve fitting API only supports 1-D curve. I get around this by linearising the equation. This implementation is for isotropic (spherical) or anistropic (longer in x/y) diagonally covariant Gaussians but not fully covariant Gaussians (anisotropic and rotated). 


Stochastic optical reconstruction microscopy (STORM) and related methods achieves sub-diffraction-limit image resolution through sequential activation and localization of individual fluorophores. The analysis of image data from these methods has typically been confined to the sparse activation regime where the density of activated fluorophores is sufficiently low such that there is minimal overlap between the images of adjacent emitters. Recently several methods have been reported for analyzing higher density data, allowing partial overlap between adjacent emitters. However, these methods have so far been limited to two-dimensional imaging, in which the point spread function (PSF) of each emitter is assumed to be identical.

In this work, we present a method to analyze high-density super-resolution data in three dimensions, where the images of individual fluorophores not only overlap, but also have varying PSFs that depend on the z positions of the fluorophores.


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Classification of trajectoire: need tracking results as input and will then classify the trajectories as  brownian motion, confined brownian or directed.

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