Kalman Smoother Based Force Localization and Mapping Using Intravital Video Microscopy

Motility is an important property of immune system cells. It provides cells with the ability to perform their function not only at the right time but also at the right place. In this paper, we introduce the problem of modeling and estimating an effective force field directing cell movement by the analysis of intravital video microscopy. A computational approach is proposed for solving this problem without dealing with a parametrized spatial model of the field in order to avoid potential errors due to inaccurate spatial model assumptions. We consider the dynamics of cells similar to the dynamics of distributed agents typically used in the field of swarm robotics. The method utilizes a fixed-interval Kalman filter based smoother. Its application results in a map giving the intensity and direction of the effective force field. The results show that real-time video images are a source of data, enabling us to visualize intriguing spatiotemporal phenomena inside immune system organs. The proposed approach can fill the existing gap between contemporary technology and quantitative data analyses present in the field of biosystems.