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

Description

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 Chanouard et al (2014) as "method 9" and is described in detail in its supplementary PDF (page 65).

Dependencies

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. Use update site to install this plugin.
  4. jama.jar. Preinstalled in Fiji.

Advantages:

  • 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 dependent of ImageJ.

Pitfalls:

  • 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

Quantitative analysis of focal adhesion dynamics

Description

The quantification is explained in detail in chapter 8 "Cell Polarity - Focal Adhesion and Actin Dynamics in Migrating Cells" in "Bioimage Data Analysis Book" downloadable from here.

For codes and sample images, download the zipped archive (linked under "Download").

has function

TrackMate

Description

TrackMate provides the tools to perform single particle tracking (SPT). SPT is an image analysis challenge where the goal is to segment and follow over time some labeled, spot-like structures. Each spot is segmented in multiple frames and its trajectory is reconstructed by assigning it an identity over these frames, in the shape of a track. These tracks can then be either visualized or yield further analysis results such as velocity, total displacement, diffusion characteristics, division events, etc...