Inverse Parameter Fitting of Biological Tissues: A Response Surface Approach
| Autor: | Nielen Stander, Bahar Fata, Daniel R. Einstein, Ivan Vesely, Alan D. Freed |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Diagnostic Imaging
Aortic valve Quantitative Biology::Tissues and Organs Physics::Medical Physics Constitutive equation Biomedical Engineering Displacement (vector) Aortic sinus Materials Testing medicine Animals Humans Computer Simulation Mathematics Computer simulation business.industry Mathematical analysis Models Cardiovascular Structural engineering Sinus of Valsalva Finite element method Nonlinear system medicine.anatomical_structure Aortic Valve Stress Mechanical business Algorithms Test data |
| Zdroj: | Annals of Biomedical Engineering. 33:1819-1830 |
| ISSN: | 1573-9686 0090-6964 |
| Popis: | In this paper, we present the application of a semi-global inverse method for determining material parameters of biological tissues. The approach is based on the successive response surface method, and is illustrated by fitting constitutive parameters to two nonlinear anisotropic constitutive equations, one for aortic sinus and aortic wall, the other for aortic valve tissue. Material test data for the aortic sinus consisted of two independent orthogonal uniaxial tests. Material test data for the aortic valve was obtained from a dynamic inflation test. In each case, a numerical simulation of the experiment was performed and predictions were compared to the real data. For the uniaxial test simulation, the experimental targets were force at a measured displacement. For the inflation test, the experimental targets were the three-dimensional coordinates of material markers at a given pressure. For both sets of tissues, predictions with converged parameters showed excellent agreement with the data, and we found that the method was able to consistently identify model parameters. We believe the method will find wide application in biomedical material characterization and in diagnostic imaging. |
| Databáze: | OpenAIRE |
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