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The idea of using VR-based surgical simulators for training of prospective surgeons has been a topic of research for more than a decade. However, surgical simulation is still far from being integrated into the medical curriculum. A number of still open questions exist, for instance the level of simulation realism which is needed for effective learning, the identification of the surgical skill components which are to be trained, as well as the validation of the training effect. Current research strives to address these problems with a new generation of highly realistic simulators. A key element of realism is the fidelity and variability of the training scene, reflecting differences in individual patients. In this book the main components of the generation process focusing on case-by-case scenarios have been described.

Combining the three presented strategies allows the definition of variable training scenes for VR-based surgical simulation. The discussed methods have been applied to obtain scenarios for different surgical simulator systems. The main focus of the related developments is hysteroscopy simulation, for which the setup will be briefly presented.

Keywords

Collision Detection Surgical Simulator Texture Synthesis Wall Perforation Scene Geometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2008

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