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Estimating Force Fields of Living Cells - Comparison of Several Regularization Schemes Combined with Automatic Parameter Choice

机译:估计活细胞的力场-几种正则化方案与自动参数选择相结合的比较

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In this paper we evaluate several regularization schemes applied to the problem of force estimation, that is Traction Force Microscopy (TFM). This method is widely used to investigate cell adhesion and migration processes as well as cellular response to mechanical and chemical stimuli. To estimate force densities TFM requires the solution of an inverse problem, a deconvolution. Two main approaches have been established for this. The method introduced by Dembo [1] makes a finite element approach and inverts the emerging LES by means of regularization. Hence this method is very robust, but requires high computational effort. The other ansatz by Butler [2] works in Fourier space to solve the problem by direct inversion. It is therefore based on the assumption of smooth data with little noise. The combination of both, a regularization in Fourier space, has been proposed [3] but not analyzed in detail. We cover this analysis and present several methods for an objective and automatic choice of the required regularization parameters.
机译:在本文中,我们评估了应用于力估计问题的几种正则化方案,即牵引力显微镜(TFM)。该方法被广泛用于研究细胞粘附和迁移过程以及细胞对机械和化学刺激的反应。为了估算力密度,TFM需要解决反问题,即反卷积。为此建立了两种主要方法。 Dembo [1]引入的方法是一种有限元方法,并通过正则化来反转新兴的LES。因此,该方法非常健壮,但是需要大量的计算工作。 Butler [2]的另一个ansatz在傅立叶空间中通过直接反演来解决问题。因此,它基于平滑数据且噪声很小的假设。已经提出了两者的组合,即在傅立叶空间中的正则化[3],但没有详细分析。我们涵盖了此分析,并提出了几种用于客观自动选择所需正则化参数的方法。

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