Live cell tracking based on cellular state recognition from microscopic images

The analysis of cell motion is an essential process in fundamental medical studies because most active cellular functions involve motion. In this paper, a computer-assisted motion analysis system is proposed for cell tracking. In the proposed tracking process, unlike in conventional tracking methods, cellular states referring to the cellular life cycle are defined and appropriate strategies are adopted for cells at different states. The use of cellular state recognition allows detection of possible cell division and hence can improve the robustness of cell tracking. Experimental results show that cells can be successfully segmented and tracked over a long period of time, and the proposed system is found to be as accurate as manual tracking. Various quantitative analyses and visualizations are used to represent cell motion, which demonstrates the usefulness of the proposed system in the study of cell dynamics.