An Estimation of Cell Forces with Hierarchical Bayes Approach Considering Cell Morphology

Abstract

Traction Force Microscopy (TFM) is one of popular techniques for measuring mechanical forces in a cell. TFM estimates the traction forces a cell produces from the displacements of the fluorescent nano beads in the culture gel substrate of the cell. However, the estimation is difficult due to the limitation in the distirubtion of beads. To improve the estimation accuracy, we proposed a Bayesian estimation method that introduces priors to the cell morphology and the force directions and simultaneously estimates the forces and the parameters with the expectation-maximization algorithm. Our method significantly improved the accuracy in our numerical experiments using synthetic and experimental datasets compared with the conventional ridge regression method.