Abstract
Cells are basic constituents of tissue in the body. To adapt to the changes of extracellular microenvironment, cells will regulate their intracellular mechanical and physiological mechanisms to control their activities, and cellular microrheology is a technique to examine these intracellular mechanical properties. Advantages of particle tracking microrheology are its non-invasiveness and locality to living cells. The purpose of this study is to develop a system of video particle tracking microrheology and its corresponding algorithms to infer cellular mechanical properties. To begin with, we reviewed the theory and physical meaning of microrheology. Then, we described the procedure of our proposed algorithms and design concepts in detail. For algorithm validation, the proposed algorithms were used to track the simulated images of fluorescence particles undergoing Brownian motion with various types of noise contamination. Finally, the proposed algorithms were applied to the process of real images of fluorescence particles embedded in living cell. Results of the experiments indicated that our algorithms could reach similar conclusions as those presented in the literature.