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Carnegie Mellon Robotics Institute

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Abstract

Automated visual-tracking of cell populations in vitro using phase contrast time-lapse microscopy is vital for quantitative, systematic and high-throughput measurements of cell behaviors. These measurements include the spatiotemporal quantification of migration, mitosis, apoptosis, and cell lineage. This paper presents an automated cell tracking system that can simultaneously track and analyze thousands of cells. The system performs tracking by cycling through frame-by-frame track compilation and spatiotemporal track linking, combining the power of two tracking paradigms. We applied the system to a range of cell populations including adult stem cells. The system achieved tracking accuracies in the range of 83.8%, outperforming previous work by up to 8%.

Notes

Associated Center(s) / Consortia: Medical Robotics Technology Center

Associated Lab(s) / Group(s): Tissue Engineering

Associated Project(s): Cell Tracking

Number of pages: 8

Text Reference

Kang Li, Mei Chen, and Takeo Kanade, "Cell Population Tracking and Lineage Construction with Spatiotemporal Context," Proceedings of the 10th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2007, pp. 295 - 302.

BibTeX Reference

@inproceedings{Li_2007_5925,
   author = "Kang Li and Mei Chen and Takeo Kanade",
   title = "Cell Population Tracking and Lineage Construction with Spatiotemporal Context",
   booktitle = "Proceedings of the 10th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)",
   pages = "295 - 302",
   year = "2007",
}

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