Elastic stiffness characterization using three-dimensional full-field deformation obtained with optical coherence
Jiawei Fu1, Fabrice Pierron2, Pablo D Ruiz1
1Loughborough University, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough, LE11 3TU, United Kingdom.
Journal of Biomedical Optics
|December 19, 2013
Summary
This study introduces a novel method for identifying material stiffness using 3D deformation data from optical coherence tomography. The technique accurately measures elastic properties in silicone phantoms, even with noise.
Area of Science:
- Biomedical Engineering
- Materials Science
- Optical Metrology
Background:
- Accurate material stiffness identification is crucial for understanding tissue mechanics and designing medical devices.
- Optical Coherence Tomography (OCT) provides high-resolution, depth-resolved 3D imaging.
- Digital Volume Correlation (DVC) analyzes volumetric data to quantify deformation fields.
Purpose of the Study:
- To develop and validate a methodology for stiffness identification using 3D full-field deformation data.
- To assess the impact of noise and reconstruction uncertainties on DVC performance.
- To determine elastic constitutive parameters of silicone rubber phantoms.
Main Methods:
- Acquisition of 3D OCT volume reconstructions of silicone rubber phantoms.
- Application of Digital Volume Correlation (DVC) to obtain full-field deformation maps.
- Utilizing a 3D manually defined Virtual Fields Method (VFM) for parameter identification.
- Evaluation of DVC performance using stationary and rigid body translation tests.
Main Results:
- Established the minimum measurable strain for reliable DVC analysis.
- Successfully identified elastic constitutive parameters from 3D deformation fields in silicone phantoms.
- Demonstrated good agreement between VFM results and analytical calculations under uniaxial tension.
Conclusions:
- The proposed methodology enables accurate stiffness identification from OCT-based 3D deformation data.
- The study provides insights into the reliability of DVC in the presence of noise and uncertainties.
- This approach offers a robust tool for characterizing material properties in soft tissues and biomaterials.
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