  This paper introduces a novel framework for the automated tracking of cells,
with a particular focus on the challenging situation of phase contrast
microscopic videos. Our framework is based on a topology preserving variational
segmentation approach applied to normal velocity components obtained from
optical flow computations, which appears to yield robust tracking and automated
extraction of cell trajectories. In order to obtain improved trackings of local
shape features we discuss an additional correction step based on active
contours and the image Laplacian which we optimize for an example class of
transformed renal epithelial (MDCK-F) cells. We also test the framework for
human melanoma cells and murine neutrophil granulocytes that were seeded on
different types of extracellular matrices. The results are validated with
manual tracking results.
