Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space

J Theor Biol. 2009 Aug 21;259(4):811-9. doi: 10.1016/j.jtbi.2009.05.005. Epub 2009 May 18.


Quantitative estimation of cellular traction has significant physiological and clinical implications. As an inverse problem, traction force recovery is essentially susceptible to noise in the measured displacement data. For traditional procedure of Fourier transform traction cytometry (FTTC), noise amplification is accompanied in the force reconstruction and small tractions cannot be recovered from the displacement field with low signal-noise ratio (SNR). To improve the FTTC process, we develop an optimal filtering scheme to suppress the noise in the force reconstruction procedure. In the framework of the Wiener filtering theory, four filtering parameters are introduced in two-dimensional Fourier space and their analytical expressions are derived in terms of the minimum-mean-squared-error (MMSE) optimization criterion. The optimal filtering approach is validated with simulations and experimental data associated with the adhesion of single cardiac myocyte to elastic substrate. The results indicate that the proposed method can highly enhance SNR of the recovered forces to reveal tiny tractions in cell-substrate interaction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Adhesion / physiology*
  • Cells, Cultured
  • Elasticity
  • Fourier Analysis
  • Microscopy, Atomic Force
  • Myocytes, Cardiac / physiology*
  • Rats
  • Stress, Mechanical