Cell Population Tracking and Lineage Construction Using Multiple-Model Dynamics Filters and Spatiotemporal Optimization
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 85.9%?2.5%, outperforming previous work by up to 9%. The proposed tracking methodology is valuable for tissue engineering, stem cell research, drug discovery and development, and related areas.
BibTeX
@workshop{Li-2007-9817,author = {Kang Li and Takeo Kanade},
title = {Cell Population Tracking and Lineage Construction Using Multiple-Model Dynamics Filters and Spatiotemporal Optimization},
booktitle = {Proceedings of 2nd International Workshop on Microscopic Image Analysis with Applications in Biology (MIAAB '07)},
year = {2007},
month = {September},
}