Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12530/30815
Title: Full L1-regularized Traction Force Microscopy over whole cells.
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Issue Date: 10-Aug-2017
Citation: BMC Bioinformatics.2017 Aug;(18)1:365
Abstract: Traction Force Microscopy (TFM) is a widespread technique to estimate the tractions that cells exert on the surrounding substrate. To recover the tractions, it is necessary to solve an inverse problem, which is ill-posed and needs regularization to make the solution stable. The typical regularization scheme is given by the minimization of a cost functional, which is divided in two terms: the error present in the data or data fidelity term; and the regularization or penalty term. The classical approach is to use zero-order Tikhonov or L2-regularization, which uses the L2-norm for both terms in the cost function. Recently, some studies have demonstrated an improved performance using L1-regularization (L1-norm in the penalty term) related to an increase in the spatial resolution and sensitivity of the recovered traction field. In this manuscript, we present a comparison between the previous two regularization schemes (relying in the L2-norm for the data fidelity term) and the full L1-regularization (using the L1-norm for both terms in the cost function) for synthetic and real data.
PMID: 28797233
URI: https://hdl.handle.net/20.500.12530/30815
Rights: openAccess
Appears in Collections:Fundaciones e Institutos de Investigación > IIS H. General U. Gregorio Marañón > Artículos
Fundaciones e Institutos de Investigación > IIS H. U. La Princesa > Artículos

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