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

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Part of the book series:Lecture Notes in Computer Science ((LNCS,volume 1496))

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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.

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Authors and Affiliations

  1. Virtual Centre for Health Informatics Department of Medical Informatics and Image Analysis, Aalborg University, Denmark

    Kim Vang Hansen & Ole Vilhelm Larsen

Authors
  1. Kim Vang Hansen

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  2. Ole Vilhelm Larsen

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Editor information

William M. Wells Alan Colchester Scott Delp

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© 1998 Springer-Verlag Berlin Heidelberg

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Hansen, K.V., Larsen, O.V. (1998). Using region-of-interest based finite element modelling for brain-surgery simulation. In: Wells, W.M., Colchester, A., Delp, S. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI’98. MICCAI 1998. Lecture Notes in Computer Science, vol 1496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056214

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