ABSTRACT
In the last years high efforts have been taken to develop surgical simulators for computer assisted training. However, most of these simulators use simple models of the human's anatomy, which are manually created using modeling software. Nevertheless, medical experts need to perform the training directly with the patient's complex anatomy, which can be received, for example, from digital imaging datasets (CT, MR). A common technique to display these datasets is volume rendering. However, even with high-end hardware only static models can be handled interactively. In surgical simulators a dynamic component is also needed because tissues must be deformed and partially removed. With the combination of springmass models, which are improved by neuro-fuzzy systems, and the recently developed OpenGL Volumizer, surgical simulation using real-time deformable (or dynamic) volume rendering became possible. As an application example the simulator ROBOSIM for minimally invasive neurosurgery is presented.
