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.
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© 2008 Springer-Verlag London Limited
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(2008). Conclusion. In: Surgical Scene Generation for Virtual Reality-Based Training in Medicine. Springer, London. https://doi.org/10.1007/978-1-84800-107-7_5
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DOI: https://doi.org/10.1007/978-1-84800-107-7_5
Publisher Name: Springer, London
Print ISBN: 978-1-84800-106-0
Online ISBN: 978-1-84800-107-7
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