Tracking cell motion using GM-PHD

Radford Ray Juang, Andre Levchenko, Philippe Burlina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a method for tracking the movement of multiple cells and their lineage. We use the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter, a multi-target tracking algorithm, to track the motion of multiple cells over time and to keep track of the lineage of cells as they spawn. We describe a spawning model for the GM-PHD filter as well as modifications to the original GM-PHD algorithm to track lineage. Experimental results are provided illustrating the approach for dense cell colonies.

Original languageEnglish (US)
Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2009
Pages1154-1157
Number of pages4
DOIs
StatePublished - Nov 17 2009
Event2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States
Duration: Jun 28 2009Jul 1 2009

Publication series

NameProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Other

Other2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
CountryUnited States
CityBoston, MA
Period6/28/097/1/09

Keywords

  • Tracking
  • Tracking filters

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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    Juang, R. R., Levchenko, A., & Burlina, P. (2009). Tracking cell motion using GM-PHD. In Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 (pp. 1154-1157). [5193262] (Proceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009). https://doi.org/10.1109/ISBI.2009.5193262