Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2002-11-11
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1361-8415
pubmed:author
pubmed:copyrightInfo
Copyright 2002 Elsevier Science B.V.
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
375-88
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Coupling of fluid and elastic models for biomechanical simulations of brain deformations using FEM.
pubmed:affiliation
Universität Hamburg, FB Informatik, AB Kognitive Systeme, Vogt-Kölln-Strasse 30, 22527 Hamburg, Germany. hagemann@informatik.uni-hamburg.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't