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Item A Mixed Reality Anatomy Teaching Tool(The Eurographics Association, 2006) Thomas, Rhys G.; John, Nigel W.; Lim, Ik Soo; Louise M. Lever and Mary McDerbyIn this paper we present an inexpensive Mixed Reality software tool for training medical students in anatomy. The software integrates the ARToolkit and Visualization Toolkit (VTK) to create a novel interactive environment in which the user can manipulate the position and orientation of the volume rendering using a plastic model of the organ to be observed. The volume rendering can then be clipped relative to an arbitrary plane to reveal data from its interior, using a second prop.Item Anatomy Education using Rapid Prototyping(The Eurographics Association, 2007) Thomas, Rhys G.; John, Nigel W.; Lim, Ik Soo; Ik Soo Lim and David DuceRapid Prototyping is a technique which is rapidly gaining interest amongst the medical community for many different purposes. In this paper we present a novel tool that uses rapidly prototyped models to serve as an interaction device for the teaching of anatomy. The user interacts with volume data of real human organs in an Augmented Reality environment delivered via a Head-Mounted Display. We include a description of how all of the key parts of the system operate and describe their integration. Our hypothesis is that this approach provides an effective and compelling alternative to cadaver based anatomy education.Item A Flexible Approach to High Performance Visualization Enabled Augmented Reality(The Eurographics Association, 2007) Hughes, Chris J.; John, Nigel W.; Ik Soo Lim and David DuceCommonly registration and tracking within Augmented Reality (AR) applications have been built around computer vision techniques that use limited bold markers, which allow for their orientation to be estimated in real-time. All attempts to implement AR without specific markers have increased the computational requirements and some information about the environment is still needed. In this paper we describe a method that not only provides a flexible platform for supporting AR but also seamlessly deploys High Performance Computing (HPC) resources to deal with the additional computational load, as part of the distributed High Performance Visualization (HPV) pipeline used to render the virtual artifacts. Repeatable feature points are extracted from known views of a real object and then we match the best stored view to the users viewpoint using the matched feature points to estimate the objects pose. We also show how our AR framework can then be used in the real world by presenting a markerless AR interface for Transcranial Magnetic Stimulation (TMS).Item Adaptive Infrastructure for Visual Computing(The Eurographics Association, 2007) Brodlie, K. W.; Brooke, J.; Chen, M.; Chisnall, D.; Hughes, C. J.; John, Nigel W.; Jones, M. W.; Riding, M.; Roard, N.; Turner, M.; Wood, J. D.; Ik Soo Lim and David DuceRecent hardware and software advances have demonstrated that it is now practicable to run large visual computing tasks over heterogeneous hardware with output on multiple types of display devices. As the complexity of the enabling infrastructure increases, then so too do the demands upon the programmer for task integration as well as the demands upon the users of the system. This places importance on system developers to create systems that reduce these demands. Such a goal is an important factor of autonomic computing, aspects of which we have used to influence our work. In this paper we develop a model of adaptive infrastructure for visual systems. We design and implement a simulation engine for visual tasks in order to allow a system to inspect and adapt itself to optimise usage of the underlying infrastructure. We present a formal abstract representation of the visualization pipeline, from which a user interface can be generated automatically, along with concrete pipelines for the visualization. By using this abstract representation it is possible for the system to adapt at run time. We demonstrate the need for, and the technical feasibility of, the system using several example applications.Item Virtual Femoral Palpation Simulation for Interventional Radiology Training(The Eurographics Association, 2010) Coles, Timothy R.; Gould, Derek A.; John, Nigel W.; Caldwell, Darwin G.; John Collomosse and Ian GrimsteadA femoral palpation simulation for training purposes has been developed to simulate the initial steps of the Seldinger technique which is currently neglected in both commercial and academic medical training simulations. The simulation co-locates visual and haptic feedback through the use of an augmented reality video see-through visualisation whilst requiring no headwear to be worn. The visual simulation implements shadowing of the users real hand in the virtual world to increase depth perception, textured deformable tissue and visually realistic cloth, whilst haptic feedback combines both tactile and force feedback based on in-vivo measured force and tactile data. The simulation is a work in progress and is to undergo validation.Item Touching The Invisible - Molecular Haptics(The Eurographics Association, 2009) Davies, R. Andrew; Maskery, James S.; John, Nigel W.; Wen Tang and John CollomosseNovel, simple, cost-effective applications combining haptics and computer graphics for the study of key chemical concepts such as reactivity and periodicity at AS/A-level and undergraduate level are described.Item Simulation of X-ray Attenuation on the GPU(The Eurographics Association, 2009) Vidal, Franck; Garnier, Manuel; Freud, Nicolas; Létang, Jean Michel; John, Nigel W.; Wen Tang and John CollomosseIn this paper, we propose to take advantage of computer graphics hardware to achieve an accelerated simulation of X-ray transmission imaging, and we compare results with a fast and robust software-only implementation. The running times of the GPU and CPU implementations are compared in different test cases. The results show that the GPU implementation with full floating point precision is faster by a factor of about 60 to 65 than the CPU implementation, without any significant loss of accuracy. The increase in performance achieved with GPU calculations opens up new perspectives. Notably, it paves the way for physically-realistic simulation of X-ray imaging in interactive time.