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Carnegie Mellon Robotics Institute

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Abstract

Automated visual-tracking of cell population in vitro using phase-contrast time-lapse microscopy is vital for the quantitative and systematic study of cell behaviors, including spatiotemporal quantification of migration, proliferation, and apoptosis. The low image quality, high and varying density of the cell culture, and the complexity of cell behaviors pose many challenges to existing tracking techniques. This paper presents a fully-automated multitarget tracking system that can simultaneously track hundreds of cells and efficiently cope with these challenges. The approach exploits a fast topology-constrained level-set method in conjunction with a stochastic motion filter, with a careful formulation that makes it suitable for real-time tracking during acquisition. Our methodology was applied to human tissue cell tracking in vitro under various imaging conditions and yielded a 88.4% tracking accuracy.

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, Eric Miller, Lee Weiss, Phil Campbell, and Takeo Kanade, "Online Tracking of Migrating and Proliferating Cells Imaged with Phase-Contrast Microscopy," Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW '06), June, 2006, pp. 65 - 72.

BibTeX Reference

@inproceedings{Li_2006_5489,
   author = "Kang Li and Eric Miller and Lee Weiss and Phil Campbell and Takeo Kanade",
   title = "Online Tracking of Migrating and Proliferating Cells Imaged with Phase-Contrast Microscopy",
   booktitle = "Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW '06)",
   pages = "65 - 72",
   month = "June",
   year = "2006",
}

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