A Bayesian traction force microscopy method with automated denoising in a user-friendly software package

DOI10.1016/J.CPC.2020.107313zbMath1525.62051arXiv2005.01377OpenAlexW3016299189MaRDI QIDQ6040068

Yunfei Huang, Benedikt Sabass, Gerhard Gompper

Publication date: 24 May 2023

Published in: Computer Physics Communications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.01377

zbMATH Keywords

Bayesian inferencetraction force microscopy

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Numerical methods for ill-posed problems for boundary value problems involving PDEs (65N20)

Cites Work

• Limitations of the \(L\)-curve method in ill-posed problems
• Determining substrate displacement and cell traction fields -- a new approach
• Regularization tools version \(4.0\) for matlab \(7.3\)
• Non-convergence of the L-curve regularization parameter selection method

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