Welcome to MIC-MAC: A Pipeline for High-throughput Microglia Morphology Analysis

MIC-MAC is an open source pipeline implemented Matlab that provides graphical user interfaces for each analysis step allowing biologists to easily process large imaging data and segment, characterize and classify thousands of microglia cell in mammalian brain samples.


Microglia, the brain resident immune cells, ensure the protection and repair of the central nervous system. However, activated microglia can also harm neurons and become toxic. Morphological modifications of microglia are a predictive read-out of their behaviour, and often serve as first evidence for their role in disease progression. Such morphological analyses and classifications in in situ tissues typically rely on incomplete visual inspections that do neither sufficiently quantify the complexity and diversity of morphological changes nor comprehensively analyse large 3d immunostained-samples. To address this challenge, we developed MIC-MAC, a Microglia and Immune Cells Morphology Analyser and Classifier pipeline that segments, characterizes and classifies all microglia and immune cells in large Iba1 immunostained 3D stacks of post-mortem fixed brain samples.


• Matlab based: MIC-MAC has been tested on Matlab version 2015 – 2018, uses the open source Octave Networks Toolbox and is optimized to include segmentation masks generated by the freely available Ilastik tool.

• User-friendly graphical user interfaces.

• Reliable segmentation of up to 99% of microglia in brain tissues by an iterative procedure.

• Comprehensive characterization of individual cells by 62 geometrical and graph-based features.

• Unbiased classification into morphologically homogenous subgroups.

• Easy visual validation by automatically generated overlays of imaging data and classified morphologies.

• Statistical comparison between physiological conditions.

License and citation

MIC-MAC is open source,uses the open source Octave Networks Toolbox (https://github.com/aeolianine/octave-networks-toolbox) and is optimized to include segmentation masks generated by the freely available Ilastik tool (http://ilastik.org).

If you use (parts of) this software in your research, please cite our publication:

Salamanca et al. (2019), MIC-MAC: High-throughput analysis of three-dimensional microglia morphologies in mammalian brains (Glia 67(8):1496-1509)


• The Matlab code of MIC-MAC is available as a zip file here.

• An imaging data set example for testing MIC-MAC will be available here soon.

How to get started?

• Read the User Guide tutorial.


If you need more information, please contact david.bouvier@uni.lu or alexander.skupin@uni.lu