Article
Improved Finite-Element mesh generation of the skullbase using a novel algorithm
Verbesserte Finite-Elemente-Netzgenerierung der Schädelbasis unter Verwendung eines neuartigen Algorithmus
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Authors
Published: | April 23, 2004 |
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Outline
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Objective
The current imaging technologies provide high-resolution data that allows biomechanic analysis for medical purposes using the Finite-Element modeling technique. However, Finite-Element modeling of complex anatomical structures is not solved satisfyingly so far as mesh quality and time effort have to be balanced. Thus application of Finite-Element analysis of individual clinical cases is limited. Voxel-based algorithms as opposed to contour-based algorithms allow an automated mesh-generation based on the image-data but their geometric precision is limited.
Methods
We developed an automated and universally applicable geometric mesh-generator that combines advantages of a voxel-based mesh generation with improved representation of the geometry by displacement of Finite-Element nodes on the object-surface. Models of an artificial 3D-pipe-section and a skullbase were generated with different mesh-densities using the newly developed geometric, unsmoothed and smoothed voxel generators. Finite Element analysis was performed and statistically compared for the individual mesh generators.
Results
The benefits of the developed mesh generator as compared to the existing algorithms were shown by statistical analysis. Comparison of the calculation results of the skullbase models showed mean element-energy errors of 2.24 Nmm, 2.14 Nmm, 1.22 Nmm for unsmoothed, smoothed and geometric voxel generators. The best representation of the anatomy as seen in the original data was achieved using the geometric voxel mesh-generator. Merely the oval foramen on the right was not rendered correctly, no pseudoforamina were generated. Furthermore the calculation of the analytic 3D-pipe-section model also resulted in the lowest element-energy error and volume error for the geometric generator as compared to smoothed and unsmoothed voxel generators.
Conclusions
The developed geometric mesh-generator is universally applicable. Furthermore it allows an automated and accurate modeling by combining advantages of the voxel-based mesh generation technique and improved geometric surface-modeling. It could therefore be beneficial for the application of Finite-Element analysis of individual clinical cases.