Automated Tracking of Red Blood Cells in Images.

Computer simulations of processes inside microfluidic devices often require validation data from experiments with biological cells. Besides single cell experiments, data involving flow of many cells can be used to validate many-cell behaviour. Manual data gathering from such experiments, such as video sequence of cell flow, is inefficient and needs to be automated. Building on top of an automated detection of red blood cells, tracking of red blood cells is needed in order to provide physical data about each cell. In this work, we first describe our existing traditional algorithms for cell tracking. We assess the possible metrics for measuring their performance and iterate upon the flaws of our algorithm in order to design improvements and propose a neural network solution.