gms | German Medical Science

55. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie e. V. (DGNC)
1. Joint Meeting mit der Ungarischen Gesellschaft für Neurochirurgie

Deutsche Gesellschaft für Neurochirurgie (DGNC) e. V.

25. bis 28.04.2004, Köln

Finite-Element mesh generation of the spine: Comparison of a newly developed algorithm to exsisting algorithms

Finite-Elemente-Netzgenerierung der Wirbelsäule: Vergleich eines neu entwickelten Algorithmus mit exsistierenden Algorithmen

Meeting Abstract

  • corresponding author Jan Kaminsky - Abteilung Neurochirurgie, Medizinische Hochschule Hannover, Hannover
  • T. Rodt - Abteilung Neurochirurgie, Medizinische Hochschule Hannover, Hannover
  • J. Zajaczek - Abteilung Neuroradiologie, Medizinische Hochschule Hannover, Hannover
  • M. Zumkeller - Abteilung Neurochirurgie, Medizinische Hochschule Hannover, Hannover

Deutsche Gesellschaft für Neurochirurgie. Ungarische Gesellschaft für Neurochirurgie. 55. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie e.V. (DGNC), 1. Joint Meeting mit der Ungarischen Gesellschaft für Neurochirurgie. Köln, 25.-28.04.2004. Düsseldorf, Köln: German Medical Science; 2004. DocP 14.154

Die elektronische Version dieses Artikels ist vollständig und ist verfügbar unter:

Veröffentlicht: 23. April 2004

© 2004 Kaminsky et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen ( Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.




The spine represents an anatomical structure where biomechanical analysis is of obvious therapeutic relevance. Contrary to generalised analysis-models using anatomical specimens, the Finite-Element modeling technique can be applied for individual biomechanical analysis. Current imaging technology provides high-resolution data that allows in-vivo analysis for medical purposes. However, modeling of complex anatomical structures is limited by the necessity to balance mesh quality and time effort so far. An algorithm that combines enhanced mesh-quality and time efficiency is presented.


A novel, automated and universally applicable geometric mesh-generator was developed combining advantages of a voxel-based mesh generation with improved representation of the anatomical geometry. Previously presented voxel-based algorithms as opposed to contour-based algorithms allowed an automated mesh-generation based on the image-data but their geometric precision was limited. By a new technique that creates a displacement of nodes on the object-surface the geometric precision is increased. Models of an artificial 3D-pipe-section and different sections of the spine were generated with varying mesh-densities using the newly developed geometric, unsmoothed and smoothed voxel generators. Finite Element analysis of different sections of the spine and the artificial 3D-pipe-section were performed and statistically compared for the individual mesh generators.


Statistical analysis showed the benefits of the developed mesh generator of the spine. When comparing the results of the analytic calculation of the 3D-pipe-section model and the results obtained by the different algorithms, a route mean square error of the surface stress of 1.23 – 4.40 MPa for the unsmoothed voxel models, 0.79 – 3.70 MPa for the smoothed voxel models with small volume error and 0.88 – 1.54 MPa for the geometric models was found. The highest element-energy error, representing a criterion to assess the mesh-quality, was 2.61*10-2, 2.46*10-2 and 1.81*10-2 Nmm for unsmoothed, smoothed and geometric voxel models respectively. The geometric voxel models of the spine sections resulted in the lower element-energy errors and volume errors compared to smoothed and unsmoothed voxel models. Furthermore the achievable detail in anatomical representation was best using the geometric voxel algorithm.


The presented geometric mesh-generator allows an automated and accurate modeling of the spine by combining advantages of the voxel-based mesh generation and improved geometric surface-modeling. It could therefore be helpful for biomechanic simulation in individual patients in order to optimize the therapeutic strategy taking the biomechanic demands into account.