An Inverse Method to Determine Material Properties of Soft Tissues

Ruggiero, Leonardo; Sol, Hugo; Sahli, Hichem; Adriaenssens, Sigrid; Adriaenssens, Nele

doi:10.1007/978-1-4614-0219-0_3

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Being pertinent to model the behavior of a wide range of materials, for instance the soft tissues and polymers, the Mooney–Rivlin model is one of the conventional hyperelastic models in the literature [34–39]. Two historical attributes have made this model a distinguished one: (1) it is one of the primarily introduced hyperelastic models; (2) it could meticulously predict the nonlinear demeanor observed from some materials, specifically the isotropic rubber-like materials.…”

Section: Methodsmentioning

confidence: 99%

An Iterative Method for Estimating Nonlinear Elastic Constants of Tumor in Soft Tissue from Approximate Displacement Measurements

Dastjerdi

Fallah

Rashidi

2019

Journal of Healthcare Engineering

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Objectives Various elastography techniques have been proffered based on linear or nonlinear constitutive models with the aim of detecting and classifying pathologies in soft tissues accurately and noninvasively. Biological soft tissues demonstrate behaviors which conform to nonlinear constitutive models, in particular the hyperelastic ones. In this paper, we represent the results of our steps towards implementing ultrasound elastography to extract hyperelastic constants of a tumor inside soft tissue. Methods Hyperelastic parameters of the unknown tissue have been estimated by applying the iterative method founded on the relation between stress, strain, and the parameters of a hyperelastic model after (a) simulating the medium's response to a sinusoidal load and extracting the tissue displacement fields in some instants and (b) estimating the tissue displacement fields from the recorded/simulated ultrasound radio frequency signals and images using the cross correlation-based technique. Results Our results indicate that hyperelastic parameters of an unidentified tissue could be precisely estimated even in the conditions where there is no prior knowledge of the tissue, or the displacement fields have been approximately calculated using the data recorded by a clinical ultrasound system. Conclusions The accurate estimation of nonlinear elastic constants yields to the correct cognizance of pathologies in soft tissues.

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Section: Methodsmentioning

confidence: 99%

An Iterative Method for Estimating Nonlinear Elastic Constants of Tumor in Soft Tissue from Approximate Displacement Measurements

Dastjerdi

Fallah

Rashidi

2019

Journal of Healthcare Engineering

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“…Using relations (15) and (16), the domain of the integration in Eq. 14changes to the known reference configuration as follows:…”

Section: Finite Element Formulation For Direct Deformation Analysis Omentioning

confidence: 99%

“…Tran et al [15] modeled the three layers of human skin with a nearly incompressible neo-Hookean material and characterized their model parameters in vivo using indentation tests. Ruggiero et al [16] and Chen et al [17] employed an indentation procedure and an inverse method to obtain material parameters of rubber-like materials. Liu et al [18] developed an algorithm for tissue parameters identification using a rolling indentation test.…”

Section: Introductionmentioning

confidence: 99%

Identification of Material Parameters of a Hyper-Elastic Body With Unknown Boundary Conditions

Hajhashemkhani

Hematiyan

Goenezen

2018

Journal of Applied Mechanics

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Identification of material properties of hyper-elastic materials such as soft tissues of the human body or rubber-like materials has been the subject of many works in recent decades. Boundary conditions generally play an important role in solving an inverse problem for material identification, while their knowledge has been taken for granted. In reality, however, boundary conditions may not be available on parts of the problem domain such as for an engineering part, e.g., a polymer that could be modeled as a hyper-elastic material, mounted on a system or an in vivo soft tissue. In these cases, using hypothetical boundary conditions will yield misleading results. In this paper, an inverse algorithm for the characterization of hyper-elastic material properties is developed, which takes into consideration unknown conditions on a part of the boundary. A cost function based on measured and calculated displacements is defined and is minimized using the Gauss–Newton method. A sensitivity analysis is carried out by employing analytic differentiation and using the finite element method (FEM). The effectiveness of the proposed method is demonstrated through numerical and experimental examples. The novel method is tested with a neo–Hookean and a Mooney–Rivlin hyper-elastic material model. In the experimental example, the material parameters of a silicone based specimen with unknown boundary condition are evaluated. In all the examples, the obtained results are verified and it is observed that the results are satisfactory and reliable.

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“…Inverse and direct finite element analysis based on the algorithms of identification of thermal and diffusive properties of investigated products and prediction of the product behaviour during heat and water transport processes (Nguyen and Boyce, 2011;Olek et al, 2005Olek et al, , 2011Ruggiero et al, 2011;Siatkowski et al, 2010a;Weres and Olek, 2005;Weres et al, 2009). Problems of estimation of unknown or unreliable property values were discussed in the papers, and further research is needed to improve the algorithms for reducing the uncertainty of mathematical modelling.…”

Section: Introductionmentioning

confidence: 99%

Integration of experimental and computational methods for identifying geometric, thermal and diffusive properties of biomaterials

Weres¹,

Kujawa²,

Olek³

et al. 2016

International Agrophysics

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A b s t r a c t. Knowledge of physical properties of biomaterials is important in understanding and designing agri-food and wood processing industries. In the study presented in this paper computational methods were developed and combined with experiments to enhance identification of agri-food and forest product properties, and to predict heat and water transport in such products. They were based on the finite element model of heat and water transport and supplemented with experimental data. Algorithms were proposed for image processing, geometry meshing, and inverse/direct finite element modelling. The resulting software system was composed of integrated subsystems for 3D geometry data acquisition and mesh generation, for 3D geometry modelling and visualization, and for inverse/direct problem computations for the heat and water transport processes. Auxiliary packages were developed to assess performance, accuracy and unification of data access. The software was validated by identifying selected properties and using the estimated values to predict the examined processes, and then comparing predictions to experimental data. The geometry, thermal conductivity, specific heat, coefficient of water diffusion, equilibrium water content and convective heat and water transfer coefficients in the boundary layer were analysed. The estimated values, used as an input for simulation of the examined processes, enabled reduction in the uncertainty associated with predictions.

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An Inverse Method to Determine Material Properties of Soft Tissues

Cited by 5 publications

References 18 publications

An Iterative Method for Estimating Nonlinear Elastic Constants of Tumor in Soft Tissue from Approximate Displacement Measurements

An Iterative Method for Estimating Nonlinear Elastic Constants of Tumor in Soft Tissue from Approximate Displacement Measurements

Identification of Material Parameters of a Hyper-Elastic Body With Unknown Boundary Conditions

Integration of experimental and computational methods for identifying geometric, thermal and diffusive properties of biomaterials

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