Characterization of single cell dynamic morphology by local deformation pattern modeling

Computational analysis of cell dynamic morphology in time-lapse images has become a new topic of biomedical research. For single cell, it is a challenging task to consider the spatial inconsistency and the temporal accumulation of cell deformation. This paper introduces an innovative automate analysis method, in which temporal features of contour point deformation are captured and then local deformation pattern is modeled to characterize cell dynamic morphology and predict cell activation statue. We applied the method to classify lymphocyte videos of multiple groups. Experimental results demonstrate that the proposed method overcomes existing methods in accuracy and robustness.