Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space |
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Authors: | Jianyong Huang Lei Qin Xiaoling Peng Tao Zhu Chunyang Xiong Youyi Zhang Jing Fang |
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Affiliation: | a Department of Biomedical Engineering, Peking University, Beijing 100871, PR China b Academy for Advanced Interdisciplinary Studies, Peking University, 100871, PR China c Institute of Vascular Medicine, Peking University Third Hospital, Beijing 100083, PR China |
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Abstract: | 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. |
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Keywords: | Cell-substrate interaction Digital image correlation Signal-noise ratio Traction force microscopy |
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