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Bioinformatics. 2011 Feb 15;27(4):564-71. doi: 10.1093/bioinformatics/btq691. Epub 2010 Dec 24.

Ct3d: tracking microglia motility in 3D using a novel cosegmentation approach.

Author information

  • 1Department of Biophysics, Institute of Neuroscience, Shanghai Institutes for Biological Sciences, 200031 Shanghai, China.

Abstract

MOTIVATION:

Cell tracking is an important method to quantitatively analyze time-lapse microscopy data. While numerous methods and tools exist for tracking cells in 2D time-lapse images, only few and very application-specific tracking tools are available for 3D time-lapse images, which is of high relevance in immunoimaging, in particular for studying the motility of microglia in vivo.

RESULTS:

We introduce a novel algorithm for tracking cells in 3D time-lapse microscopy data, based on computing cosegmentations between component trees representing individual time frames using the so-called tree-assignments. For the first time, our method allows to track microglia in three dimensional confocal time-lapse microscopy images. We also evaluate our method on synthetically generated data, demonstrating that our algorithm is robust even in the presence of different types of inhomogeneous background noise.

AVAILABILITY:

Our algorithm is implemented in the ct3d package, which is available under http://www.picb.ac.cn/patterns/Software/ct3d; supplementary videos are available from http://www.picb.ac.cn/patterns/Supplements/ct3d.

PMID:
21186244
[PubMed - indexed for MEDLINE]
PMCID:
PMC3035800
Free PMC Article
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