A hybrid collision detection method for virtual laparoscopic surgery.

摘要

With advances in computing power and graphical capabilities, it is possible to develop a Virtual Reality (VR)-based realistic trainer for surgical training. Laparoscopic surgery is taking over open surgery techniques due to its reduced morbidity and recovery time. Collision detection has always been a challenging field of research in VR-based applications. In particular, surgical simulations involving collisions between complex deformable objects require intense computation when compared to those between non-deformable objects. It is essential to assist the medical surgeon with visual realism by providing accurate collision points in real-time. This research work addresses the problem of detecting collisions between a deformable mesh and the organs over which it needs to be placed. The approach presented, is generic and can also be employed to other kinds of collision queries. Though, various collision detection methods have been proposed in the past, they have not proven suitable for real-time speeds during the mesh placement task in Laparoscopic inguinal hernia surgery. We have therefore developed a hybrid approach utilizing the OpenGL based graphic hardware test and hierarchical bounding volumes to output accurate collision points in real time.