Segmentation, tracking, and analysis of focal adhesion dynamics in cellular microscopy imaging
Cell adhesion, a process mediated by the formation of discrete structures known as focal adhesions (FAs), is pivotal to many biological events including cell motility. Much is known about the molecular composition of FAs, although our knowledge of the spatio-temporal recruitment and the amount of the individual components present in the FAs is still incomplete. To fill this gap, an essential prerequisite is a reliable procedure for the recognition, segmentation, and tracking of FAs. While manual segmentation and tracking may provide some advantages when done by an expert, its performance is usually hindered by subjective judgement and long time required to analyse large data sets. Here, we develop a model-based segmentation and tracking algorithm that overcomes these problems. We found that our algorithm matches FA segmentation done by an expert. In addition, it contains a dedicated computational approach to correct single frame segmentation errors that may arise from the analysis of poorly defined FAs. We believe that our work establishes the basis for a comprehensive qualitative and quantitative analysis of FA dynamics and the later development of mathematical models that simulate FAs behaviour.