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What is it?

TrakEM2 is an ImageJ plugin for morphological data mining, three-dimensional modeling and image stitching, registration, editing and annotation.


Four movies:

See a lot more snapshots and movies.

TrakEM2 video tutorials for users.

Example data sets

Latest news

Download latest Fiji with TrakEM2 or go to menu "Help - Update Fiji".
Pull source code from the git repos.
Stay up to date with Fiji.
TrakEM2 class diagram for programmers.
TrakEM2 video tutorials for users.

2012-07-04 - 1.0a released

Milestone release: 1.0a. TrakEM2 is now feature complete.

Thanks to Stephan Saalfeld for the final touches to his image registration library and graphical interface!

2011-04-12 - Open Connectome Project hosts an ssTEM image data set online with CATMAID

The Open Connectome Project is hosting an ssTEM image data set of 1200 serial sections from Bock et al. (Nature 2011). The data was analyzed with TrakEM2, using the Treeline and Connector data types to reconstruct neuronal arborizations and their synapses of the mouse visual cortex.

The image data set is deployed online with CATMAID, the Collaborative Annotation Toolkit for Massive Amouts of Image Data. TrakEM2 is able to export its image data set to CATMAID with "Export - Flat Image" (with "For web"), and Treeline, AreaTree and Connector instances are currently exported with custom scripts.

Read all news here.

Download and Install

Managed installation:
For a manual installation:
See the TrakEM2 Installation How-To for all details and required additional files.

What can you do with it?

And much more...

How does it work?

TrakEM2 has been written in Java as an ImageJ plugin, and contains a virtualization engine for seamlessly working with arbitrarily large datasets, limited only by your file storage capacity.

Two independent modalities exist: either XML-based projects, working directly with the file system, or database-based projects, working on top of a local or remote PostgreSQL database.


TrakEM2 is the design child of Rodney Douglas and Albert Cardona, with the help of the entire Institute of Neuroinformatics, University of Zurich / ETH, and has been implemented by Albert Cardona.

Stephan Saalfeld and Stephan Preibisch, from Pavel Tomančák's group, have written the libraries responsible for phase-correlation, cross-correlation, scale invariant feature transform, and associated utilities such as proper, gaussian-exact image resizing and automatically multithreaded processing routines that adapt to the machine's available cores.

Cite TrakEM2

If your work uses TrakEM2 or its associated image registration libraries, cite the following primary reference publication:

Additionally, if your primary use of TrakEM2 is for aligning and registering collections of images, please cite as well the following publications:

Some aspects of TrakEM2 are explained and illustrated by the following publications:

Who uses TrakEM2

See the list of publications that cite TrakEM2.


TrakEM2 would not have been possible without the continuous help from ImageJ's author, Wayne Rasband, and the economic support to Albert Cardona from both Rodney Douglas at INI and Volker Hartenstein (NIH Grant NS054814) at the University of California Los Angeles.
We are also particularly grateful to German Koestinger for testing and extensive feedback, David Lawrence for his assistance in PostgreSQL, and also to Nuno da Costa, Rita Bopp, Lauriston Kellaway, John Anderson, Wayne Pereanu and Davi Bock for their input.

3D visualization and mesh-making by marching cubes have been possible thanks to Bene Schmid and Johannes Schindelin from Würzburg.
Image stitching has been made possible thanks to Stephan Preibisch, and the web viewer thanks to Stephan Saalfeld, both from Pavel Tomančák's in the Max Plank Institute for Cell Biology and Genetics, Dresden.


Please forward any comments and suggestions to acardona at ini phys ethz ch.