Merging of intersecting triangulations for finite element modeling.
Surface mesh generation over intersecting triangulations is a problem common to many branches of biomechanics. A new strategy for merging intersecting triangulations is described. The basis of the method is that object surfaces are represented as the zero-level iso-surface of the distance-to-surface function defined on a background grid. Thus, the triangulation of intersecting objects reduces to the extraction of an iso-surface from an unstructured grid. In a first step, a regular background mesh is constructed. For each point of the background grid, the closest distance to the surface of each object is computed. Background points are then classified as external or internal by checking the direction of the surface normal at the closest location and assigned a positive or negative distance, respectively. Finally, the zero-level iso-surface is constructed. This is the final triangulation of the intersecting objects. The overall accuracy is enhanced by adaptive refinement of the background grid elements. The resulting surface models are used as support surfaces to generate three-dimensional grids for finite element analysis. The algorithms are demonstrated by merging arterial branches independently reconstructed from contrast-enhanced magnetic resonance images and by adding extra features such as vascular stents. Although the methodology is presented in the context of finite element analysis of blood flow, the algorithms are general and can be applied in other areas as well.
Cebral
J R
JR
School of Computational Sciences, George Mason University, 4400 University Drive, MS 4C7, Fairfax, VA 22030, USA. jcebral@gmu.edu
Löhner
R
R
Choyke
P L
PL
Yim
P J
PJ
D000465:Algorithms; D001696:Biomechanical Phenomena; D002339:Carotid Arteries / Q000033:anatomy & histology / Q000502:physiology; D020342:Finite Element Analysis; D006439:Hemodynamics; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008954:Models, Biological; D008955:Models, Cardiovascular