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FAST, the Feature-Assisted Segmenter/Tracker

Have you struggled with automated measurement of the movement of many closely-packed individuals? The Durham lab's tracking system, FAST, may be the answer to your problems. Its features include:

  • A user-friendly GUI, designed to minimise the number of parameters that must be chosen and maximise immediate user feedback for those that do.
  • Flexible design, accommodating a range of different workflows and dataset types.
  • Rapid algorithms with low memory requirements, allowing thousands of objects to be tracked simultaneously on a standard laptop computer.
  • Integrated overlay and plotting systems, allowing rapid validation and visualisation of tracking data.
  • No need for a Matlab license - FAST is also available as a free stand-alone application.

Sound good? Download the latest distribution of the Matlab files here, the stand-alone version here, or see the installation guide for more details on how to perform the download and setup process.

FIXME

Segmentation

The segmentation module allows you to automatically cut out objects from your images.

Feature detection

Feature detection quantifies properties of the objects detected by the segmentation module.

Tracking

Tracking links individuals through time, allowing you to monitor objects as they evolve. A sub-GUI also allows manual correction of tracks.

Division detection

Many biological samples consist of cells that repeatedly divide. This module allows you to detect these divisions and reconstruct lineages.

Overlays

Overlaying extracted data on top of raw images can provide powerful visualisations of your system.

Plotting

|usage:plotting The plotting module allows you to quickly assess relationships between features and variables extracted during tracking.

We are grateful for funding from the EPSRC and BBSRC, grant codes EP/F500394/1 and BB/R018383/1.

https://bbsrc.ukri.org/

https://epsrc.ukri.org/

https://www.sheffield.ac.uk/physics/

http://www.dtc.ox.ac.uk/

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  • Last modified: 2020/06/29 18:24
  • by pseudomoaner