2D and 3D tracking based on global cost function optimization

Perrine's picture
Workflow URL: 
Workflow Author: 

Perrine Paul-Gilloteaux

Workflow Language: 
3D time series
Input data type: 
2D+ time, 3D + time
Output data type: 
text files
Applicable to (Sample Data):: 
Comment / Instructions: 

The workflow consists of firstly identifying spot (which can be also gravity center of cells identified by another method), and then secondly compute trajectories by linking these spots by global optimisation with a cost function. This method is part of the methods evaluated in [1] and is described in detail in its supplementary section.


Following plugins are required.

  1. JAR to be placed under IJ plugin directory
    1. A pdf file with instructions and output description is also available in the zip .
  2. MTrackJ : Used for visualization of tracks. Preinstalled in Fiji.
  3. Imagescience.jar: This library is used by MTrackJ. Preinstalled in Fiji.
  4. jama.jar. Preinstalled in Fiji.


  • support blinking (with a parameters allowing it or not)
  • fast,
  • can be used in batch, some analysis results provided.
  • No dynamic model.
  • The tracking part is not dependant of ImageJ.


  • does not support division,
  • the optimization algorithm used is a simulated annealing, so results can be slightly different between two runs.
  • No Dynamic model (so less good results but can be used for a first study of the kind of movements)

The sample data

The parameters used for this example data Beads, were

  1. detection: 150
  2. the max distance in pixels: 20
  3. max allowed disappearance in frame: 1


No votes yet