Evaluation of image registration for measuring deformation fields in soft tissue mechanics

TL;DR

This paper evaluates the effectiveness of non-rigid image registration for measuring deformation fields in soft tissues, comparing it to digital image correlation, and highlights its advantages for complex biological tissue analysis.

Contribution

It introduces a non-rigid image registration approach for full-field deformation measurement in soft tissues, demonstrating comparable accuracy to DIC and advantages in handling irregular shapes and small samples.

Findings

Image registration achieves similar accuracy to DIC for sub-pixel deformations.

The method allows analysis of entire sample regions, including complex heterogeneous deformations.

It is effective for soft tissues with irregular shapes and small dimensions.

Abstract

High-fidelity biomechanical models usually involve the mechanical characterization of biological tissues using experimental methods based on optical measurements. In most experiments, strains are evaluated based on displacements of a few markers and represents an average within the region of interest (ROI). Full-field measurements may improve description of non-homogeneous materials such as soft tissues. The approach based on non-rigid Image Registration is proposed and compared with standard Digital Image Correlation (DIC) on a set of samples, including (i) complex heterogeneous deformations with sub-pixel displacement, (ii) a typical uniaxial tension test of aorta, and (iii) an indentation test on skin. The possibility to extend the ROI to the whole sample and the exploitation of a natural tissue pattern represents the main assets of the proposed method whereas the results show similar accuracy as standard DIC when analysing sub-pixel deformations. Therefore, displacement and strain fields measurement based on Image Registration is very promising to characterize heterogeneous specimens with irregular shapes and/or small dimensions, which are typical features of soft biological tissues.