Imaging of moving cells requires continuous adjustments to keep cells and/or intracellular bodies of interest within the imaging field and in focus. We will develop methods to control microscopes via Andor's acquisition software to track the objects of interest in order to get better knowledge about cell migration, but also to keep them in the centre of the imaging field by performing continuous adjustments. Using available imaging data (JUELICH, UKA), we will investigate the use of tracking algorithms to compute movement and extract trajectories from multiple cells moving in a 3D environment. In order to automatically analyse local shape changes of single keratinocytes during migration, we will test algorithms to compute local growth rates and to detect newly emerging structures such as filopodia, lamellipodial protrusions, and fluorescently-labelled focal adhesions and cytoskeletal filaments from 2D and possibly 3D images of migrating cells. We will optimise ways to visualise the resulting information to make it easily accessible to the researcher. Shape descriptors will be defined to allow the characterisation and comparison of the evolution of cell shape during motion cycles of real and stimulated cells.

The main novelties we wish to introduce are the following:

• Provide a novel tracking framework with better performance, by investigating, among other elements, data association methods

• Develop a novel segmentation algorithm

• Integrate the tracking and segmentation in an efficient way