Colocalisation analysis

Colocalization analysis
Co-localisation analysis



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.


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.


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.


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:


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