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A Tizzard

Publications and source records attributed to A Tizzard.

4 recordsLinked to original sources

Generating accurate finite element meshes for the forward model of the human head in EIT.

The use of realistic anatomy in the model used for image reconstruction in EIT of brain function appears to confer significant improvements compared to geometric shapes such as a sphere. Accurate model geometry may be achieved by numerical models based on magnetic resonance images (MRIs) of the head, and this group has elected to use finite element meshing (FEM) as it enables detailed internal anatomy to be modelled and has the capability to incorporate information about tissue anisotropy. In this paper a method for generating accurate FEMs of the human head is presented where MRI images are manually segmented using custom adaptation of industry standard commercial design software packages. This is illustrated with example surface models and meshes from adult epilepsy patients, a neonatal baby and a phantom latex tank incorporating a real skull. Mesh quality is assessed in terms of element stretch and hence distortion.

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Solving the forward problem in electrical impedance tomography for the human head using IDEAS (integrated design engineering analysis software), a finite element modelling tool.

If electrical impedance tomography is to be used as a clinical tool, the image reconstruction algorithms must yield accurate images of impedance changes. One of the keys to producing an accurate reconstructed image is the inclusion of prior information regarding the physical geometry of the object. To achieve this, many researchers have created tools for solving the forward problem by means of finite element methods (FEMs). These tools are limited, allowing only a set number of meshes to be produced from the geometric information of the object. There is a clear need for geometrical accurate FEM models to improve the quality of the reconstructed images. We present a commercial tool called IDEAS, which can be used to create FEM meshes for these models. The application of this tool is demonstrated by using segmented data from the human head to model impedance changes inside the head.

Algorithms↗