Active Contours for Cell Tracking

This paper introduces an active contour or snakebased method for tracking cells within a video sequence. Specifically, we apply our cell tracking techniques to rolling leukocytes observed in vivo (in living animal) from video microscopy. The analysis of leukocyte motion reveals cues about the mechanism of inflammatory disease. To attack the problem of tracking leukocytes in vivo, the proposed snake tracker utilizes shape and size information specific to the leukocytes. The principal contribution of this work lies in introducing the shape and size constraint as a geometric primitive in the parametric snake energy model. The energy functional is then minimized through the basic principles of the calculus of variations to obtain the Euler equations used in contour updating. We have developed a partial differential equation (PDE) based generalized gradient vector flow (GVF) that accommodates for contrast changes and weak cell edges. Whereas previous GVF models are sensitive to initial contour placement, the modified GVF construction with Dirichlet type boundary condition (BC) allows a snake tracker to be robust for a wide range of initial positions. Another contribution in this work is to incorporate an energy term in the snake model that eliminates the need for explicitly resampling the snake contour intermittently as performed in traditional snake evolution. Using animal experiments, we compare the accuracy of the proposed snake tracker with the correlation and centroid based tracker and show that the proposed tracker is superior in terms of increased number of frames tracked and reduced localization error.