Applications of Automatic Mesh Generation and Adaptive Methods in Computational Medicine

Important problems in Computational Medicine exist that can beneet from the implementation of adaptive mesh reenement techniques. Biological systems are so inherently complex that only eecient models running on state of the art hardware can begin to simulate reality. To tackle the complex geometries associated with medical applications we present a general purpose mesh generation scheme based upon the Delaunay tessellation algorithm and an iterative point generator. In addition, automatic, two-and three-dimensional adaptive mesh reenement methods are presented that are derived from local and global estimates of the nite element error. Mesh generation and adaptive reenement techniques are utilized to obtain accurate approximations of bioelectric elds within anatomically correct models of the heart and human thorax. Speciically, we explore the simulation of cardiac deebrillation and the general forward and inverse problems in electrocardiography (ECG). Comparisons between uniform and adaptive reenement techniques are made to highlight the computational eeciency and accuracy of adaptive methods in the solution of eld problems in computational medicine.