In order to improve the accuracy of image-guided neurosurgery, different biomechanical models have been developed to correct preoperative images with respect to intraoperative changes like brain shift or tumor resection. All existing biomechanical models simulate different anatomical structures by using either appropriate boundary conditions or by spatially varying material parameter values, while assuming the same physical model for all anatomical structures. In general, this leads to physically implausible results, especially in the case of adjacent elastic and fluid structures. Therefore, we propose a new approach which allows to couple different physical models. In our case, we simulate rigid, elastic and fluid regions by using the appropriate physical description for each material, namely either the Navier equation or the Stokes equation. To solve the resulting differential equations, we derive a linear matrix system for each region by applying the finite element method (FEM). Thereafter, the linear matrix systems are linked together, ending up with one overall linear matrix system. Our new approach has been tested and compared to a purely linear elastic model using synthetic as well as tomographic images. It turns out from our experiments, that the integrated treatment of rigid, elastic and fluid regions improves the physical plausibility of the predicted deformation results as compared to a purely linear elastic model.
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http://dx.doi.org/10.1016/s1361-8415(02)00059-2 | DOI Listing |
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