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Surgical training on the World Wide Web

By Nuha H. El-Khalili

Abstract

The World Wide Web as a repository of information has had a great influence on our lives. This influence is increasing as the web introduces applications in addition to information. These applications have several advantages, such as world wide accessibility, distance group learning and collaboration. Furthermore, the web encourages training applications since it offers multi-media that can support all stages of training.\ud \ud On the other hand, the virtual reality technology has been utilised to provide new systematic training methods for surgical procedures. These solutions are usually\ud expensive in terms of cost and computation. In this thesis we propose a novel solution to fulfill the training needs of radiologists performing one type of minimally invasive surgery known as interventional radiology. Our training method combines the capabilities of virtual reality to provide realistic simulation environment together with the web environment to provide platform independent, scalable and accessible system.\ud \ud In this thesis we analyse this type of surgical procedure in order to deduce the training requirements of such an application. Then, we investigate the possibility of fulfilling these requirements within the server-client architecture of the web environment. We study the degree to which current web technologies- such as Java and VRML- can support the development of a three-dimensional virtual environment with complex interactions. Furthermore, we study the plausibility of providing high computational behaviour modelling training environment on the web by utilising physically-based modelling techniques.\ud \ud We also discuss the effect of adopting the web environment on fulfilling the virtual reality and training requirements of our system. Finally, we evaluate the resulting system to find out how useful is the proposed solution from the clinical point of view

Publisher: School of Computing (Leeds)
Year: 1999
OAI identifier: oai:etheses.whiterose.ac.uk:643

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