Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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MRI Content-Adaptive Finite Element Mesh Generation Toolbox

  • Lee W.H. (Functional and Metabolic Imaging Center Department of Biomedical Engineering, Kyung Hee University) ;
  • Kim T.S. (Functional and Metabolic Imaging Center Department of Biomedical Engineering, Kyung Hee University) ;
  • Cho M.H. (Functional and Metabolic Imaging Center Department of Biomedical Engineering, Kyung Hee University) ;
  • Lee S.Y. (Functional and Metabolic Imaging Center Department of Biomedical Engineering, Kyung Hee University)
  • Published : 2006.06.01
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Abstract

Finite element method (FEM) provides several advantages over other numerical methods such as boundary element method, since it allows truly volumetric analysis and incorporation of realistic electrical conductivity values. Finite element mesh generation is the first requirement in such in FEM to represent the volumetric domain of interest with numerous finite elements accurately. However, conventional mesh generators and approaches offered by commercial packages do not generate meshes that are content-adaptive to the contents of given images. In this paper, we present software that has been implemented to generate content-adaptive finite element meshes (cMESHes) based on the contents of MR images. The software offers various computational tools for cMESH generation from multi-slice MR images. The software named as the Content-adaptive FE Mesh Generation Toolbox runs under the commercially available technical computation software called Matlab. The major routines in the toolbox include anisotropic filtering of MR images, feature map generation, content-adaptive node generation, Delaunay tessellation, and MRI segmentation for the head conductivity modeling. The presented tools should be useful to researchers who wish to generate efficient mesh models from a set of MR images. The toolbox is available upon request made to the Functional and Metabolic Imaging Center or Bio-imaging Laboratory at Kyung Hee University in Korea.

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