Understanding the dynamics of cell behaviour has the potential to lead to identifying the mechanisms of diseases such as cancer and of immune function. The increasingly sophisticated measurement techniques in life science has given rise to high resolution high throughput screening and in-vivo time lapse image sequences. Such image sequences contain single cell and population level information. Changes in patterns of cell behaviour can be associated with potential effectiveness of a therapeutic drug.
The aim of this project is to analyse such image sequences and extract cell motion / shape characteristics and their change over time for individual cells and across the cell population. It will require tracking the cell motion and characterising their behaviour patterns. Additionally, the cell shape features will be identified and associated with cell motion. Correlations between motion patterns and cell shapes will be analysed and quantified. An important aspect will be to quantitatively assess changes in cell behaviour under different drug environments. This understanding will then be incorporated into swarm robots for suitable applications.