Send to:

Choose Destination
See comment in PubMed Commons below
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.



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.


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.


Our algorithm is implemented in the ct3d package, which is available under; supplementary videos are available from

[PubMed - indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for HighWire Icon for PubMed Central
    Loading ...
    Write to the Help Desk