Reliable tracking of large scale dense antiparallel particle motion for fluorescence live cell imaging

Ge Yang, Alexandre Matov, Gaudenz Danuser

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

22 Scopus citations

Abstract

This paper presents a technique that reliably tracks large numbers of particles undergoing dense antiparallel motion and frequent appearance and disappearance. Such techniques are essential to many applications of fluorescence cellular and molecular imaging for automated quantitative analysis of dynamic cellular functions. The basic tracking algorithm of this technique integrates motion models at particle, local and global levels. It establishes correspondence between particles based on state similarity and resolves correspondence conflicts using optimal graph assignment. A statistical and robust approach for algorithm parameter setting is developed through establishing the equivalence of the algorithm to a Kalman-filtering based tracker under assumptions that are biologically supported. Online track initiation and propagation depend critically on computing the global vector field of particle flow using a new optimal-flow minimum-cost graph algorithm. Vector field denoising and interpolation are performed using anisotropic filtering after clustering. The technique has been experimentally verified and successfully applied to the tracking of Fluorescent Speckle Microscopy images of live cells.

Original languageEnglish (US)
Title of host publication2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
PublisherIEEE Computer Society
ISBN (Electronic)0769526608
DOIs
StatePublished - 2005
Externally publishedYes
Event2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops - San Diego, United States
Duration: Sep 21 2005Sep 23 2005

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2005-September
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - Workshops
Country/TerritoryUnited States
CitySan Diego
Period9/21/059/23/05

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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