Visualization and simulation techniques for surgical simulators using actual patient's data

Because of the increasing complexity of surgical interventions research in surgical simulation became more and more important over the last years. However, the simulation of tissue deformation is still a challenging problem, mainly due to the short response times that are required for real-time interaction. The demands to hard and software are even larger if not only the modeled human anatomy is used but the anatomy of actual patients. This is required if the surgical simulator should be used as training medium for expert surgeons rather than students. In this article, suitable visualization and simulation methods for surgical simulation utilizing actual patient's datasets are described. Therefore, the advantages and disadvantages of direct and indirect volume rendering for the visualization are discussed and a neuro-fuzzy system is described, which can be used for the simulation of interactive tissue deformations. The neuro-fuzzy system makes it possible to define the deformation behavior based on a linguistic description of the tissue characteristics or to learn the dynamics by using measured data of real tissue. Furthermore, a simulator for minimally-invasive neurosurgical interventions is presented that utilizes the described visualization and simulation methods. The structure of the simulator is described in detail and the results of a system evaluation by an experienced neurosurgeon-a quantitative comparison between different methods of virtual endoscopy as well as a comparison between real brain images and virtual endoscopies-are given. The evaluation proved that the simulator provides a higher realism of the visualization and simulation then other currently available simulators. (C) 2002 Elsevier Science B.V. All rights reserved.