2D + Time Object Tracking Using Fiji and ilastik

  • Andrea Urru
  • Miguel Angel González Ballester
  • Chong ZhangEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 2040)


Tracking cells is one of the main challenges in biology, as it often requires time-consuming annotations and the images can have a low signal-to-noise ratio while containing a large number of cells. Here we present two methods for detecting and tracking cells using the open-source Fiji and ilastik frameworks. A straightforward approach is described using Fiji, consisting of a pre-processing and segmentation phase followed by a tracking phase, based on the overlapping of objects along the image sequence. Using ilastik, a classifier is trained through manual annotations to both detect cells over the background and be able to recognize false detections and merging cells. We describe these two methods in a step-by-step fashion, using as example a time-lapse microscopy movie of HeLa cells.

Key words

Cell tracking Segmentation Classification Fiji ilastik 



This work was financed by a fellowship (LCF/BQ/IN17/11620069) from “la Caixa” Foundation (ID 100010434) and by the Spanish Ministry of Economy and Competitiveness grant MDM-1025-0502 through the Maria de Maeztu Units of Excellence in R&D program. We also acknowledge support from the European Commission through the NEUBIAS network (COST action no. CA15124).

Supplementary material (896 kb)
Electronic Supplementary File 1 (ZIP 897 kb)


  1. 1.
    Stuurman N (2003) MTrack2 Fiji plugin. Scholar
  2. 2.
    Tinevez J (2016) TrackMate Fiji plugin. Scholar
  3. 3.
    Tinevez J, Perry N, Schindelin J et al (2017) TrackMate: an open and extensible platform for single-particle tracking. Methods 115:80–90CrossRefGoogle Scholar
  4. 4.
    Sbalzarini I F (2006) Particle Tracker Fiji plugin.
  5. 5.
    Sbalzarini IF, Koumoutsakos P (2005) Feature point tracking and trajectory analysis for video imaging in cell biology. J Struct Biol 151(2):182–195CrossRefGoogle Scholar
  6. 6.
    Schindelin J, Arganda-Carreras I, Frise E (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9(7):676–682. Scholar
  7. 7.
    CellProfiler Project Website.
  8. 8.
    Hilsenbeck O et al (2016) Software tools for single-cell tracking and quantification of cellular and molecular properties. Nat Biotechnol 34(7):703–706. Scholar
  9. 9.
  10. 10.
    ilastik Toolkit.
  11. 11.
    Meijering E, Dzyubachyk O, Smal I (2012) Methods for cell and particle tracking. Methods Enzymol 504:183–200. Scholar
  12. 12.
    Chenouard N et al (2014) Objective comparison of particle tracking methods. Nat Methods 11(3):281–290. Scholar
  13. 13.
    MitoCheck Project.
  14. 14.
    Haubold C et al (2016) Segmenting and tracking multiple dividing targets using ilastik. Adv Anat Embryol Cell Biol 219:199–229Google Scholar
  15. 15.
    Fiji Homepage.
  16. 16.
    ilastik documentation: installation guide.
  17. 17.
    Gurobi Optimizer.
  18. 18.
    ilastik documentation: exporting output.
  19. 19.
    Importing image files—ImageJ.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Andrea Urru
    • 1
  • Miguel Angel González Ballester
    • 1
    • 2
  • Chong Zhang
    • 1
    Email author
  1. 1.BCN-MedTech, DTICUniversitat Pompeu FabraBarcelonaSpain
  2. 2.ICREABarcelonaSpain

Personalised recommendations