Image-based meshing is opening up exciting new possibilities for the application of computational continuum mechanics methods (finite-element and computational fluid dynamics) to a wide range of biomechanical and biomedical problems that were previously intractable owing to the difficulty in obtaining suitably realistic models. Innovative surface and volume mesh generation techniques have recently been developed, which convert three-dimensional imaging data, as obtained from magnetic resonance imaging, computed tomography, micro-CT and ultrasound, for example, directly into meshes suitable for use in physics-based simulations. These techniques have several key advantages, including the ability to robustly generate meshes for topologies of arbitrary complexity (such as bioscaffolds or composite micro-architectures) and with any number of constituent materials (multi-part modelling), providing meshes in which the geometric accuracy of mesh domains is only dependent on the image accuracy (image-based accuracy) and the ability for certain problems to model material inhomogeneity by assigning the properties based on image signal strength. Commonly used mesh generation techniques will be compared with the proposed enhanced volumetric marching cubes (EVoMaCs) approach and some issues specific to simulations based on threedimensional image data will be discussed. A number of case studies will be presented to illustrate how these techniques can be used effectively across a wide range of problems from characterization of micro-scaffolds through to head impact modelling.
Background Recent advances in diagnostic imaging and associated software have enabled the transformation of anatomical structures into finite element (FE) models facilitating computerized facial modelling. The work presented employs personalized imaging data of facial anatomical structures for use in planning and predicting the outcome of maxillofacial surgery. The current process relies on either freehand planning and/or commercial twodimensional (2D) and three-dimensional (3D) surgical planning software packages, but the validity of these software packages has been questioned. In this paper, the finite element technique was used to predict the outcome of maxillofacial surgery.
Hill's one-dimensional three-element model has often been used for formulating a three-dimensional skeletal muscle constitutive model, which generally involves several material parameters. However, only few of these parameters have physical meanings and can be experimentally determined. In this paper, a parametric study of a Hill-type hyperelastic skeletal muscle model is performed. First, the Hill-type hyperelastic skeletal muscle model is formulated, containing 13 material parameters. The values or value ranges of these parameters are discussed. The muscle model is then used to predict the behaviour of New Zealand white rabbit hind leg muscle tibialis anterior and a sensitivity study of several parameters is performed. Results show that some parameters in the muscle model can be experimentally determined, some parameters have their own value ranges and the muscle model can predict the experimental data by tuning the parameters within their value ranges. The results from the sensitivity study can help understand how some parameters influence the total muscle stress.
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