Publication: L1-regularized reconstruction for traction force microscopy
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2016-06-16
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Tutors
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IEEE
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Abstract
Traction Force Microscopy (TFM) is a technique widely used to recover cellular tractions from the deformation they cause in their surrounding substrate. Traction recovery is an ill-posed inverse problem that benefits of a regularization scheme constraining the solution. Typically, Tikhonov regularization is used but it is well known that L1-regularization is a superior alternative to solve this type of problems. For that, recent approaches have started to explore what could be their contribution to increase the sensitivity and resolution in the estimation of the exerted tractions. In this manuscript, we adapt the L1-regularization of the curl and divergence to 2D TFM and compare the recovered tractions on simulated and real data with those obtained using Tikhonov and L1-norm regularization.
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Proceeding of: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). IEEE, Prague, 13-16 April, 2016.
Keywords
Cellular biophysics, Image reconstruction, Medical image processing, Microscopy, L1-norm regularization, L1-regularized reconstruction, Tikhonov regularization, Cellular tractions, Ill-posed inverse problem, Regularization scheme, Traction force microscopy, Traction recovery, Twodimensional
Bibliographic citation
IEEE, 2016, pp. 140-144