Estimation of rheological parameters for unstained living cells

Abstract

In video-records, objects moving in intracellular regions are often hardly detectable and identifiable. To squeeze the information on the intracellular flows, we propose an automatic method of reconstruction of intracellular flow velocity fields based only on a recorded video of an unstained cell. The basis of the method is detection of speeded-up robust features (SURF) and assembling them into trajectories. Two components of motion—direct and Brownian—are separated by an original method based on minimum covariance estimation. The Brownian component gives a spatially resolved diffusion coefficient. The directed component yields a velocity field, and after fitting the vorticity equation, estimation of the spatially distributed effective viscosity. The method was applied to videos of a human osteoblast and a hepatocyte. The obtained parameters are in agreement with the literature data.