Tracking of Cell Populations to Understand their Spatio-Temporal Behavior in Response to Physical Stimuli

We have developed methods for segmentation and track-ing of cells in time-lapse phase-contrast microscopy im-ages. Our multi-object Bayesian algorithm detects and tracks large numbers of cells in presence of clutter and iden-tifies cell division. To solve the data association problem, the assignment of current measurements to cell tracks, we tested various cost functions with both an optimal and a fast, suboptimal assignment algorithm. We also propose metrics to quantify cell migration properties, such as motil-ity and directional persistence, and compared our findings of cell migration with the standard random walk model. We measured how cell populations respond to the physi-cal stimuli presented in the environment, for example, the stiffness property of the substrate. Our analysis of hundreds of spatio-temporal cell trajectories revealed significant dif-ferences in the behavioral response of fibroblast cells to changes in hydrogel conditions. 1