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Using region-of-interest based finite element modelling for brain-surgery simulation

  • Kim Vang Hansen
  • Ole Vilhelm Larsen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1496)

Abstract

Brain surgery simulation requires a mathematical model of the geometric and elastic properties of the entire brain. To allow for realtime manipulation of the model it is necessary to differentiate the level of accuracy between different subparts of the brain model. A Finite Element Model (FEM) of the brain is presented capable of differentiating the spatial and temporal accuracy in different parts of the model. In a user defined region-of-interest around the surgical target point a dynamic FEM model is used to give high accuracy. The remaining parts of the brain is modelled by a static FEM model having less accuracy. The two models are integrated into one model for the entire brain using Condensation. In the context of our early version of a brain surgery simulator we have tested the condensed model versus a full dynamic model of the brain. Promising results concerning spatial error and execution time are shown.

Keywords

Spatial Error Steady State Error Entire Brain Brain Surgery Surgery Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Kim Vang Hansen
    • 1
  • Ole Vilhelm Larsen
    • 1
  1. 1.Virtual Centre for Health Informatics Department of Medical Informatics and Image AnalysisAalborg UniversityDenmark

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