Cell tracking algorithms
Dr Chandrasekhar Venkataraman | School of Mathematics and Statistics
In the field of cell biology, modern experimental and microscopy techniques generate vast amounts of high quality images of live cell populations over time. These datasets are so vast that they are indecipherable to a human observer in their raw form. This necessitates the development of automated computational algorithms that allow us to probe and understand as much of the available data as possible. Such algorithms must allow the tracking of potentially large cell populations, recovering dynamic quantities of interest such as speed and shape.
We describe two approaches to cell tracking developed in collaboration with Ibidi, a company that develop cell assays based in Munich, Germany. Specifically, we present a method for particle tracking applicable to large datasets that recovers the trajectories of cell centroids. We also describe a novel method for whole cell tracking, in which we recover entire cell morphologies using a phase field approach. A major advantage of the methodology, which appears new within the field, is that physical aspects of cell migration can be incorporated into the algorithm. Thus, hopefully generating more faithful approximation to the true morphologies.