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. On the other hand, the virtual reality technology has been utilised to provide new systematic training methods for surgical procedures. These solutions are usually 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. 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. 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.

In this thesis, we propose a new approach to Chinese-English Biomedical cross-lingual information retrieval (CLIR) using query expansion based on the eCMeSH Tree, a Chinese-English ontology extended from the Chinese Medical Subject Headings (CMeSH) Tree. The CMeSH Tree is not designed for information retrieval (IR), since it only includes heading terms and has no term weighting scheme for these terms. Therefore, we design an algorithm, which employs a rule-based parsing technique combined with the C-value term extraction algorithm and a filtering technique based on mutual information, to extract Chinese synonyms for the corresponding heading terms. We also develop a term-weighting mechanism. Following the hierarchical structure of CMeSH, we extend the CMeSH Tree to the eCMeSH Tree with synonymous terms and their weights. We propose an algorithm to implement CLIR using the eCMeSH Tree terms to expand queries. In order to evaluate the retrieval improvements obtained from our approach, the results of the query expansion based on the eCMeSH Tree are individually compared with the results of the experiments of query expansion using the CMeSH Tree terms, query expansion using pseudo-relevance feedback, and document translation. We also evaluate the combinations of these three approaches. This study also investigates the factors which affect the CLIR performance, including a stemming algorithm, retrieval models, and word segmentation.