Error analysis of surface-distribution and non-deformation of fluorescent beads for the IC-GN2 DVC algorithm

Digital volume correlation (DVC) method is extensively used for the internal displacement measurement. In biomechanical experiments, fluorescent beads are used, instead of traditional speckles (or microstructure of materials), as the information feature of the volume image for DVC algorithm. The traditional experimental method and DVC algorithm, together, provide an effective measurement method for the cell deformation. Nevertheless, the aforesaid method has three limitations, viz., (1) low accuracy for complex displacement and poor efficiency for traditional second-order forward additive Gauss-Newton (FA-GN(2)) algorithm, (2) shape function mismatch induced by the non-deformation of fluorescent beads, and (3) the extreme phototoxicity caused by the long scanning time. To tackle these issues, we introduce the inverse compositional Gauss-Newton DVC algorithm with the second-order shape function (IC-GN(2) DVC algorithm) to achieve higher accuracy and establish the four speckle volume image models to analyze the influence of the distribution and non-deformation of fluorescent beads on the results of calculation of DVC method. Henceforth, we propose an experimental method, considering that fluorescent beads are only distributed on the surface of the gel substrate (cells are also placed on the surface of gel substrate) enabling short scanning time (termed speckle-surface-distributed experimental method). The results from the analysis by numerical simulations show that the proposed IC-GN(2) DVC algorithm has a very high accuracy (local error < 0.1 voxel). The error analysis of the four models shows that the non-deformation of fluorescent beads will induce significant error into the calculation results, whereas the surface-distribution of fluorescent beads induces little error, which prove the reliability of the speckle-surface-distributed experimental method. The noise robustness of the IC-GN(2) DVC algorithm with the speckle-surface-distributed experimental method is also studied. Finally, the migration and deformation of the living cell is analyzed using the IC-GN(2) DVC algorithm and the speckle-surface-distributed experimental method.

Automated summary

The text discusses the application of the Digital volume correlation (DVC) method in biomechanical experiments, highlighting the challenges and proposed solutions to improve accuracy and reliability. The introduction of the IC-GN(2) DVC algorithm and the speckle-surface-distributed experimental method address issues like shape function mismatch and phototoxicity. Results indicate high accuracy and reliability of the proposed methods in analyzing cell deformation and migration.