2D+time object tracking using Fiji and Ilastik

  • Authors
  • Urru A, González Ballester MA, Zhang C
  • UPF authors
  • GONZALEZ BALLESTER, MIGUEL ANGEL;
  • Authors of the book
  • Rebollo, Elena, Bosch, Manel (Eds.)
  • Book title
  • Computer Optimized Microscopy: Methods and Protocols
  • Publication year
  • 2019
  • Pages
  • 423-448
  • Abstract
  • 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.
  • Complete citation
  • Urru A, González Ballester MA, Zhang C. 2D+time object tracking using Fiji and Ilastik. In: Rebollo, Elena, Bosch, Manel (Eds.). Computer Optimized Microscopy: Methods and Protocols. 1 ed. 2019. p. 423-448.