Synonyms
Colocalization analysis
Co-localisation analysis

3D object based colocalisation

Bioimage Analyst
Developer

A user comes to the Facility: “I’ve got a set of 2 channels 3D images where objects are overlapping. I think the overlap might not be the same from object to object. I would like to quantify the physical overlap and get a map of quantifications”. Your mission: write the appropriate macro, knowing a user might always change her/his mind, and ask for more… Ready to take on the challenge ?

SODA suite

Description

Ensemble of blocks that implement SODA method for confocal and super-resolution microscopy, in 2 and 3 dimensions

Icy SODA logo

Spots colocalization (ComDet)

Description

Quote " finding and/or analyzing colocalization of bright intensity spots (cells, particles, vesicles, comets, dots, etc) in images with heterogeneous background (microscopy, astronomy, engineering, etc). "

Uses Gaussian-Mexican hat convolution for preprocessing.

CEM

Description

Computer-assisted Evaluation of Myelin formation (CEM) is a collection designed to automate myelin quantification. It requires use input to choose the best threshold values. The myelin is calculated as an overlap between neuronal signal and oligodendrocyte signal. Results are given as pixel counts and percents.

CEM runs as an imageJ plugin with an optional Matlab extension to remove cell bodies. More details are published at Kerman et al. 2015 Development. Supplemental Material includes a detailed user manual and the download link.

Myelin

MIPAV

Description

The MIPAV (Medical Image Processing, Analysis, and Visualization) application enables quantitative analysis and visualization of medical images of numerous modalities such as PET, MRI, CT, or microscopy. Using MIPAV's standard user-interface and analysis tools, researchers at remote sites (via the internet) can easily share research data and analyses, thereby enhancing their ability to research, diagnose, monitor, and treat medical disorders.

GDSC plugins

Description

Quote: "The GDSC ImageJ plugins are a collection of analysis programs for microscopy images including colocalisation analysis and peak finding (FindFoci)."

Many types of analysis besides simply finding foci detection (spot detection) is bundled in this plugin. One prominent function is "FindFoci Optimizer". This allows feeding images with spot annotation by the user (multi-point selection tool) and scans through various parameter combinations to find the best parameter set that gives the results similar to the annotation. This is almost like machine learning... but with well-established parameter types that allows you to fully understand what is going on.

JACoP

Description

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)

example of partial colocalisation from reference publication

Distance Analysis (DiAna)

Description

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