Colocalisation analysis

This ImageJ plug-in is a compilation of co-localization tools. It allows:

-Calculating a set of commonly used co-localization indicators:

Pearson's coefficient Overlap coefficient k1 & k2 coefficients Manders' coefficient Generating commonly used visualizations:

-Cytofluorogram

Having access to more recently published methods:

-Costes' automatic threshold

Li's ICA Costes' randomization Objects based methods (2 methods: distances between centres and centre-particle coincidence)

This plugin allows : Calculating co-localization between objects in 3D Measuring 3D distances between nearest object, co-localized or not Getting some 3D measurements about each objects The plugin can be used with labelled images, but it also integrates tools for the segmentation of the objects. Programming language: JAVA Processes: Denoise filter Segmentation of the objects Object based co-localization and distance analysis Counting and measurements on objects

Image-processing algorithms developed at the MOSAIC Group for fluorescence microscopy. Tools included:

• 2D/3D single-particle tracking tool which can be used to track bright spots in 2D/3D movies over time.
• Optimal filament segmentation of 2D images. 
• Curvature filters for image filtering, denoising, and restoration. 
• Image naturalization for image enhancement based on gradient statistics of natural-scence images. 
• Tool for automatically send and distribute jobs on clusters and get back the results.
• Multi-region image segmentation of 2D and 3D images without needing to know the number of regions beforehand. 
• Squassh for globally optimal segmentation of piecewise constant regions in 2D and 3D images and for object-based co-localization analysis. 
• Tool for inferring spatial interactions between patterns of objects in images or between coordinates read from a file.
• Tool for robust, histogram-based background subtraction well suited to correct for inhomogeneous illumination artifacts.
• A tool to estimate the Point-Spread Function of the microscopy out of 2D fluorescence images.
• A tool to measure the 3D Point-Spread Function of a confocal microscope from an image stack.
• Addition of synthetic Poisson-distributed noise to an image in order to simulate shot noise of various signal-to-noise ratios. 
• Convolution of an image with a Bessel function in order to simulate imaging with a microscope. 
• A utility to detect bright spots in images and estimate their center. 
• A utility to create manual segmentations to be used as ground truth to test and benchmark automatic segmentation algorithms.
• A tool for replacing one color in an image with another color.

LocAlization Microscopy Analyzer (LAMA) is a software tool that contains several well-established data post processing algorithms for single-molecule localization microscopy (SMLM) data. LAMA has implemented algorithms for cluster analysis, colocalization analysis, localization precision estimation and image registration. LAMA works with a graphical user interface (GUI), and accepts simple input data formats as supported by various single- molecule localization software tools.

MosaicIA is a tool to analyze the spatial distribution of objects in images. It estimates from an observed particle or object distribution what hypothetical interaction between the objects is most likely to have created this distribution.