Full L-1-regularized Traction Force Microscopy over whole cells Articles uri icon

authors

  • SUÑE AUÑON, ALEJANDRO
  • PEÑAS, ALVARO JORGE
  • CUENCA AGUILAR, ROCÍO
  • MANZANARES, MIGUEL VICENTE
  • VAN OOSTEWYCK, HANS
  • MUÑOZ BARRUTIA, MARIA ARRATE

publication date

  • August 2017

start page

  • 1

end page

  • 14

issue

  • 1

volume

  • 18

International Standard Serial Number (ISSN)

  • 1471-2105

abstract

  • Abstract: Background: 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.

keywords

  • traction force microscopy; spatial domain; regularization; spatial resolution; cells; cost functions; costs; cytology; image resolution; inverse problems; recovery; traction (friction); biological applications; regularization schemes; spatial domains; synthetic and real data; tikhonov regularization; molecular biology; microscope image; noise; publication; punishment; stress; traction therapy; whole cell; algorithm; animal; biomechanics; cho cell line; cricetulus; fluorescence microscopy; hamster hydrogel; algorithms; animals; biomechanical phenomena; cho cells; cricetinae; hydrogels