Diatrack particle tracking software: Review of applications and performance evaluation

Pascal Vallotton*, Antoine M. van Oijen, Cynthia B. Whitchurch, Vladimir Gelfand, Leslie Yeo, Georgios Tsiavaliaris, Stephanie Heinrich, Elisa Dultz, Karsten Weis, David Grünwald

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Object tracking is an instrumental tool supporting studies of cellular trafficking. There are three challenges in object tracking: the identification of targets; the precise determination of their position and boundaries; and the assembly of correct trajectories. This last challenge is particularly relevant when dealing with densely populated images with low signal-to-noise ratios—conditions that are often encountered in applications such as organelle tracking, virus particle tracking or single-molecule imaging. We have developed a set of methods that can handle a wide variety of signal complexities. They are compiled into a free software package called Diatrack. Here we review its main features and utility in a range of applications, providing a survey of the dynamic imaging field together with recommendations for effective use. The performance of our framework is shown to compare favorably to a wide selection of custom-developed algorithms, whether in terms of localization precision, processing speed or correctness of tracks.

Original languageEnglish (US)
Pages (from-to)840-852
Number of pages13
JournalTraffic
Volume18
Issue number12
DOIs
StatePublished - Dec 2017

Keywords

  • biological imaging
  • cell tracking
  • dynamic imaging
  • live cell imaging
  • organelle tracking
  • particle tracking
  • single molecule
  • super-resolution
  • vesicle tracking

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Genetics
  • Cell Biology

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