Uncertainty-aware traction force microscopy
Fig 7
TFM-UQ adaptively regularizes based on the local displacement uncertainty.
(A) Mean marginal posterior traction stress distribution () approximated from Hybrid-Gibbs sampling. (Based on synthetic data described in Fig 6A.) (B) Pointwise marginal posterior uncertainty (standard deviation
) of posterior traction stress (C) L-curve to determine Tikhonov regularization parameter
in traditional TFM methods.
and
are regularization parameters obtained from L-curve corners of homoskedastic synthetic simulations with spatially uniform low noise (L) or high noise (H). (D, E, F) Tikhonov regularized traction stress field corresponding to L-curve corner
, low noise
and high noise
respectively.
is the discretized Laplacian operator. (G, H, I) Tikhonov regularized traction stress field, with
identity matrix.
,
and
were determined to match 95th percentile of traction stress magnitude with the respective fields in (D-F).