Kim Vang Hansen

Modelling of interaction between a spatula and a human brain

This paper describes a method for surgery simulation, or more specifically a learning system of how to use a brain spatula. Improper use of brain spatulas can lead to brain tissue lesions such as tearing of brain tissue and ischemia. The idea is to provide surgeons with a tool which can teach them the correlation between deformation and applied force. The system includes a Finite Element based model of the brain in a Virtual Reality setup with haptic feedback. The physical model links the shape of the deformable model with the associated force. The interaction between the spatula and the brain model is handled by a collision response method which aims at smoothing the discrete haptic feedback. The experimental results are promising even though the used force feedback device is somewhat constraining the realism.

Using Region-of-Interest Based Finite Element Modeling for Brain-Surgery Simulation

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.

Region-of-interest based finite element modelling of the brain-an approach to brain surgery simulation

One of the major problems in brain surgery simulation is to achieve both real-time performance and physical realism without compromising the necessary freedom to perform topological changes like cutting. In an attempt to solve the problem we present a new method for differentiating the spatial and temporal accuracy for the brain tissue models. Finite element methods are used for the modelling with a dynamic model applied to areas which require high accuracy and a static model for the remaining areas. The two models are integrated into one for the entire brain using condensation. The dynamic model is specified as a user-defined region-of-interest. The experiments carried out have shown promising results concerning spatial error and execution time.