Microtubule Dynamics Analysis Using Kymographs and Variable-Rate Particle Filters

Ihor Smal, I Grigoriev, Anna Akhmanova, Wiro Niessen, Erik Meijering

Research output: Contribution to journalArticleAcademicpeer-review

26 Citations (Scopus)

Abstract

Studying intracellular dynamics is of fundamental importance for understanding healthy life at the molecular level and for developing drugs to target disease processes. One of the key technologies to enable this research is the automated tracking and motion analysis of these objects in microscopy image sequences. To make better use of the spatiotemporal information than common frame-by-frame tracking methods, two alternative approaches have recently been proposed, based upon either Bayesian estimation or space-time segmentation. In this paper, we propose to combine the power of both approaches, and develop a new probabilistic method to segment the traces of the moving objects in kymograph representations of the image data. It is based on variable-rate particle filtering and uses multiscale trend analysis of the extracted traces to estimate the relevant kinematic parameters. Experiments on realistic synthetically generated images as well as on real biological image data demonstrate the improved potential of the new method for the analysis of microtubule dynamics in vitro.
Original languageUndefined/Unknown
Pages (from-to)1861-1876
Number of pages16
JournalIEEE Transactions on Image Processing
Volume19
Issue number7
DOIs
Publication statusPublished - 2010

Research programs

  • EMC MGC-02-13-02
  • EMC NIHES-03-30-03

Cite this