Elastodynamic shape modeling in virtual medicine

Surgical simulation is the coming training method for medical education. The main reasons for this are the reduced risk for the patients and the easy repeatability of complicated surgical procedures. Therefore, an improved impression of reality during the simulated training must be obtained. For this, a complex model of the human's anatomy and physiology is needed. With regards to pathological conditions, which should be considered, it is necessary to build more general anatomical models. Simple static models are unsuitable for surgical simulation because convincing interactivity is only possible with deformable organs and elastic tissues. Traditional models of tissue deformation have difficulties to simulate the appearance of deformation because of the unknown physical parameters of the tissue's elasticity. Hence this paper describes a method for elastodynamic shape modeling with neuro-fuzzy systems, which are able to adapt the necessary parameters from real tissues.