Search

Background: Virtual reality (VR) technology is emerging as a powerful tool in medical training and has potential benefits for paramedic education. Aim: The aim of this paper is to report the development of ParaVR, which uses VR to maintain paramedics' skills. Methods: Computer scientists at the University of Chester and the Welsh Ambulance Services NHS Trust (WAST) developed ParaVR in four stages: identifying requirements and specifications; alpha version development; beta version development; and management—development of software, further funding and commercialisation. Results: Needle cricothyrotomy and needle thoracostomy emerged as candidates for the prototype ParaVR. The Oculus Rift head-mounted display was combined with Novint Falcon haptic device and a virtual environment crafted using 3D modelling software, which was ported to the Oculus Go virtual reality headset and the Google Cardboard VR platform. Conclusion: VR is an emerging educational tool with the potential to enhance paramedic skills development and maintenance. The ParaVR programme is the first step in the authors' development, testing and scaling up of this technology.

Surgical smoke removal algorithms can improve the quality of intra-operative imaging and reduce hazards in image-guided surgery, a highly desirable post-process for many clinical applications. These algorithms also enable effective computer vision tasks for future robotic surgery. In this article, we present a new unsupervised learning framework for high-quality pixel-wise smoke detection and removal. One of the well recognized grand challenges in using convolutional neural networks (CNNs) for medical image processing is to obtain intra-operative medical imaging datasets for network training and validation, but availability and quality of these datasets are scarce. Our novel training framework does not require ground-truth image pairs. Instead, it learns purely from computer-generated simulation images. This approach opens up new avenues and bridges a substantial gap between conventional non-learning based methods and which requiring prior knowledge gained from extensive training datasets. Inspired by the Generative Adversarial Network (GAN), we have developed a novel generative-collaborative learning scheme that decomposes the de-smoke process into two separate tasks: smoke detection and smoke removal. The detection network is used as prior knowledge, and also as a loss function to maximize its support for training of the smoke removal network. Quantitative and qualitative studies show that the proposed training framework outperforms the state-of-the-art de-smoking approaches including the latest GAN framework (such as PIX2PIX). Although trained on synthetic images, experimental results on clinical images have proved the effectiveness of the proposed network for detecting and removing surgical smoke on both simulated and real-world laparoscopic images.

Virtual reality entertainment and serious games popularity has continued to rise but the processes for level design for VR games has not been adequately researched. Our paper contributes LevelEd VR; a generic runtime virtual reality level editor that supports the level design workflow used by developers and can potentially support user generated content. We evaluated our LevelEd VR application and compared it to an existing workflow of Unity on a desktop. Our current research indicates that users are accepting of such a system, and it has the potential to be preferred over existing workflows for VR level design. We found that the primary benefit of our system is an improved sense of scale and perspective when creating the geometry and implementing gameplay. The paper also contributes some best practices and lessons learned from creating a complex virtual reality tool, such as LevelEd VR.

We present a novel self-supervised framework for monocular image depth learning and confidence estimation. Our framework reduces the amount of ground truth annotation data required for training Convolutional Neural Networks (CNNs), which is often a challenging problem for the fast deployment of CNNs in many computer vision tasks. Our DepthNet adopts a novel fully differential patch-based cost function through the Zero-Mean Normalized Cross Correlation (ZNCC) to take multi-scale patches as matching and learning strategies. This approach greatly increases the accuracy and robustness of the depth learning. Whilst the proposed patch-based cost function naturally provides a 0-to-1 confidence, it is then used to self-supervise the training of a parallel network for confidence map learning and estimation by exploiting the fact that ZNCC is a normalized measure of similarity which can be approximated as the confidence of the depth estimation. Therefore, the proposed corresponding confidence map learning and estimation operate in a self-supervised manner and is a parallel network to the DepthNet. Evaluation on the KITTI depth prediction evaluation dataset and Make3D dataset show that our method outperforms the state-of-the-art results.

Mixed Reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic-based interactive MR framework that is beyond current geometry-based approaches, offering a step-change in generating high-level context-aware interactions. Our critical insight is that by building semantic understanding in MR, we can develop a system that not only greatly enhances user experience through object-specific behaviors, but also it paves the way for solving complex interaction design challenges. In this paper, our proposed framework generates semantic properties of the real-world environment through a dense scene reconstruction and deep image understanding scheme. We demonstrate our approach by developing a material-aware prototype system for context-aware physical interactions between the real and virtual objects. Quantitative and qualitative evaluation results show that the framework delivers accurate and consistent semantic information in an interactive MR environment, providing effective real-time semantic level interactions.

Navigating a powered wheelchair and avoiding collisions is often a daunting task for new wheelchair users. It takes time and practice to gain the coordination needed to become a competent driver and this can be even more of a challenge for someone with a disability. We present a cost-effective virtual reality (VR) application that takes advantage of consumer level VR hardware. The system can be easily deployed in an assessment centre or for home use, and does not depend on a specialized high-end virtual environment such as a Powerwall or CAVE. This paper reviews previous work that has used virtual environments technology for training tasks, particularly wheelchair simulation. We then describe the implementation of our own system and the first validation study carried out using thirty three able bodied volunteers. The study results indicate that at a significance level of 5 percent then there is an improvement in driving skills from the use of our VR system. We thus have the potential to develop the competency of a wheelchair user whilst avoiding the risks inherent to training in the real world. However, the occurrence of cybersickness is a particular problem in this application that will need to be addressed.

The potential of augmented reality (AR) technology to assist minimally invasive surgery (MIS) lies in its computational performance and accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-time and accurate augmented information overlay in MIS is still a formidable task. In this Letter, the authors present a novel real-time AR framework for MIS that achieves interactive geometric aware AR in endoscopic surgery with stereo views. The authors’ framework tracks the movement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camera is predicted by minimising the re-projection error to achieve a fast tracking performance, while the three-dimensional mesh is incrementally built by a dense zero mean normalised cross-correlation stereo-matching method to improve the accuracy of the surface reconstruction. The proposed system does not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real time. With the geometric information available, the proposed AR framework is able to interactively add annotations, localisation of tumours and vessels, and measurement labelling with greater precision and accuracy compared with the state-of-the-art approaches.

We present VRIA, a Web-based framework for creating Immersive Analytics (IA) experiences in Virtual Reality. VRIA is built upon WebVR, A-Frame, React and D3.js, and offers a visualization creation workflow which enables users, of different levels of expertise, to rapidly develop Immersive Analytics experiences for the Web. The use of these open-standards Web-based technologies allows us to implement VR experiences in a browser and offers strong synergies with popular visualization libraries, through the HTML Document Object Model (DOM). This makes VRIA ubiquitous and platform-independent. Moreover, by using WebVR's progressive enhancement, the experiences VRIA creates are accessible on a plethora of devices. We elaborate on our motivation for focusing on open-standards Web technologies, present the VRIA creation workflow and detail the underlying mechanics of our framework. We also report on techniques and optimizations necessary for implementing Immersive Analytics experiences on the Web, discuss scalability implications of our framework, and present a series of use case applications to demonstrate the various features of VRIA. Finally, we discuss current limitations of our framework, the lessons learned from its development, and outline further extensions.

We describe a mixed reality environment that has been designed as an aid for training driving skills for a powered wheelchair. Our motivation is to provide an improvement on a previous virtual reality wheelchair driving simulator, with a particular aim to remove any cybersickness effects. The results of a validation test are presented that involved 35 able bodied volunteers divided into three groups: mixed reality trained, virtual reality trained, and a control group. No significant differences in improvement was found between the groups but there is a notable trend that both the mixed reality and virtual reality groups improved more than the control group. Whereas the virtual reality group experienced discomfort (as measured using a simulator sickness questionnaire), the mixed reality group experienced no side effects.

We developed an application that makes indoor modelling accessible by utilizing consumer grade technology in the form of Apple's ARKit and a smartphone to assist with serious games level design. We compared our system to that of a tape measure and a system based on an infra-red depth sensor and application. We evaluated the accuracy and efficiency of each system over four different measuring tasks of increasing complexity. Our results suggest that our application is more accurate than the depth sensor system and as accurate and more time efficient as the tape measure over several tasks. Participants also showed a preference to our LevelEd AR application over the depth sensor system regarding usability.

We report on the design, implementation and evaluation of , a framework for building immersive analytics (IA) solutions in Web-based Virtual Reality (VR), built upon WebVR, A-Frame, React and D3. The recent emergence of affordable VR interfaces have reignited the interest of researchers and developers in exploring new, immersive ways to visualize data. In particular, the use of open-standards web-based technologies for implementing VR in a browser facilitates the ubiquitous and platform-independent adoption of IA systems. Moreover, such technologies work in synergy with established visualization libraries, through the HTML document object model (DOM). We discuss high-level features of and present a preliminary user experience evaluation of one of our use cases.

Background and objective: While Minimally Invasive Surgery (MIS) offers considerable benefits to patients, it also imposes big challenges on a surgeon’s performance due to well-known issues and restrictions associated with the field of view (FOV), hand-eye misalignment and disorientation, as well as the lack of stereoscopic depth perception in monocular endoscopy. Augmented Reality (AR) technology can help to overcome these limitations by augmenting the real scene with annotations, labels, tumour measurements or even a 3D reconstruction of anatomy structures at the target surgical locations. However, previous research attempts of using AR technology in monocular MIS surgical scenes have been mainly focused on the information overlay without addressing correct spatial calibrations, which could lead to incorrect localization of annotations and labels, and inaccurate depth cues and tumour measurements. In this paper, we present a novel intra-operative dense surface reconstruction framework that is capable of providing geometry information from only monocular MIS videos for geometry-aware AR applications such as site measurements and depth cues. We address a number of compelling issues in augmenting a scene for a monocular MIS environment, such as drifting and inaccurate planar mapping. Methods: A state-of-the-art Simultaneous Localization And Mapping (SLAM) algorithm used in robotics has been extended to deal with monocular MIS surgical scenes for reliable endoscopic camera tracking and salient point mapping. A robust global 3D surface reconstruction framework has been developed for building a dense surface using only unorganized sparse point clouds extracted from the SLAM. The 3D surface reconstruction framework employs the Moving Least Squares (MLS) smoothing algorithm and the Poisson surface reconstruction framework for real time processing of the point clouds data set. Finally, the 3D geometric information of the surgical scene allows better understanding and accurate placement AR augmentations based on a robust 3D calibration. Results: We demonstrate the clinical relevance of our proposed system through two examples: (a) measurement of the surface; (b) depth cues in monocular endoscopy. The performance and accuracy evaluations of the proposed framework consist of two steps. First, we have created a computer-generated endoscopy simulation video to quantify the accuracy of the camera tracking by comparing the results of the video camera tracking with the recorded ground-truth camera trajectories. The accuracy of the surface reconstruction is assessed by evaluating the Root Mean Square Distance (RMSD) of surface vertices of the reconstructed mesh with that of the ground truth 3D models. An error of 1.24 mm for the camera trajectories has been obtained and the RMSD for surface reconstruction is 2.54 mm, which compare favourably with previous approaches. Second, in vivo laparoscopic videos are used to examine the quality of accurate AR based annotation and measurement, and the creation of depth cues. These results show the potential promise of our geometry-aware AR technology to be used in MIS surgical scenes. Conclusions: The results show that the new framework is robust and accurate in dealing with challenging situations such as the rapid endoscopy camera movements in monocular MIS scenes. Both camera tracking and surface reconstruction based on a sparse point cloud are effective and operated in real-time. This demonstrates the potential of our algorithm for accurate AR localization and depth augmentation with geometric cues and correct surface measurements in MIS with monocular endoscopes.

The requirement for training surgical procedures without exposing the patient to additional risk is well accepted and is part of a national drive in the UK and internationally. Computer-based simulations are important in this context, including neurosurgical resident training. The objective of this study is to evaluate the effectiveness of a custom-built virtual environment in assisting training of a ventriculostomy procedure. The training tool (called VCath) has been developed as an app for a tablet platform to provide easy access and availability to trainees. The study was conducted at the first boot camp organized for all year-one trainees in neurosurgery in the UK. The attendees were randomly distributed between the VCath training group and the control group. Efficacy of performing ventriculostomy for both groups was assessed at the beginning and end of the study using a simulated insertion task. Statistically significant changes in performance of selecting the burr hole entry point, the trajectory length and duration metrics for the VCath group, together with a good indicator of improved normalized jerk (representing the speed and smoothness of arm motion), all suggest that there has been a higher-level cognitive benefit to using VCath. The app is successful as it is focused on the cognitive task of ventriculostomy, encouraging the trainee to rehearse the entry point and use anatomical landmarks to create a trajectory to the target. In straight-line trajectory procedures such as ventriculostomy, cognitive task-based education is a useful adjunct to traditional methods and may reduce the learning curve and ultimately improve patient safety.

This paper presents recent additions to our Wheelchair-VR application, in particular the use of different drive configurations. We have previously shown that Wheelchair-VR can be used to improve driving skills. Here we consider the utility of the application in allowing users who are in the process of purchasing or upgrading a wheelchair to experience different configurations and options in a cost-effective virtual environment. A preliminary study is presented, which suggests that this approach can be effective.

In vascular interventional radiology, procedures generally start with the Seldinger technique to access the vasculature, using a needle through which a guidewire is inserted, followed by navigation of catheters within the vessels. Visual and tactile skills are learnt in a patient apprenticeship which is expensive and risky for patients. We propose a training alternative through a new virtual simulator supporting the Seldinger technique: ImaGiNe (imaging guided interventional needle) Seldinger. It is composed of two workstations: (1) a simulated pulse is palpated, in an immersive environment, to guide needle puncture and (2) two haptic devices provide a novel interface where a needle can direct a guidewire and catheter within the vessel lumen, using virtual fluoroscopy. Different complexities are provided by 28 real patient datasets. The feel of the simulation is enhanced by replicating, with the haptics, real force and flexibility measurements. A preliminary validation study has demonstrated training effectiveness for skills transfer.

International audience; Purpose Training in Interventional Radiology currently uses the apprenticeship model, where clinical and technical skills of invasive procedures are learnt during practice in patients. This apprenticeship training method is increasingly limited by regulatory restrictions on working hours, concerns over patient risk through trainees' inexperience and the variable exposure to case mix and emergencies during training. To address this, we have developed a computer-based simulation of visceral needle puncture procedures. Methods A real-time framework has been built that includes: segmentation, physically based modelling, haptics rendering, pseudo-ultrasound generation and the concept of a physical mannequin. It is the result of a close collaboration between different universities, involving computer scientists, clinicians, clinical engineers and occupational psychologists. Results The technical implementation of the framework is a robust and real-time simulation environment combining a physical platform and an immersive computerized virtual environment. The face, content and construct validation have been previously assessed, showing the reliability and effectiveness of this framework, as well as its potential for teaching visceral needle puncture. Conclusion A simulator for ultrasound-guided liver biopsy has been developed. It includes functionalities and metrics extracted from cognitive task analysis. This framework can be useful during training, particularly given the known difficulties in gaining significant practice of core skills in patients.

Mixed Reality (MR) is of increasing interest within technology- driven modern medicine but is not yet used in everyday practice. This situation is changing rapidly, however, and this paper explores the emergence of MR technology and the importance of its utility within medical applications. A classification of medical MR has been obtained by applying an unbiased text mining method to a database of 1,403 relevant research papers published over the last two decades. The classification results reveal a taxonomy for the development of medical MR research during this period as well as suggesting future trends. We then use the classification to analyse the technology and applications developed in the last five years. Our objective is to aid researchers to focus on the areas where technology advancements in medical MR are most needed, as well as providing medical practitioners with a useful source of reference.

This paper discusses the design issues and implementation details of building a medical training simulator. Example projects that have been undertaken by the Visualization and Medical Graphics group at Bangor University and our collaborators are used to illustrate the points made. A detailed case study is then presented of a virtual environment designed to train the Seldinger Technique, a common procedure in interventional radiology. The paper will introduce a medical practitioner to the technology behind a medical virtual environment. It will also provide an engineer with an overview of many of the issues that need to be considered when undertaking to build such an application. The paper ends with the author’s views on future developments in this exciting domain.

If we were to have a Grid infrastructure for visualization, what technologies would be needed to build such an infrastructure, what kind of applications would benefit from it, and what challenges are we facing in order to accomplish this goal? In this survey paper, we make use of the term ‘visual supercomputing’ to encapsulate a subject domain concerning the infrastructural technology for visualization. We consider a broad range of scientific and technological advances in computer graphics and visualization, which are relevant to visual supercomputing. We identify the state-of-the-art technologies that have prepared us for building such an infrastructure. We examine a collection of applications that would benefit enormously from such an infrastructure, and discuss their technical requirements. We propose a set of challenges that may guide our strategic efforts in the coming years.

The Op3D visualization system allows, for the first time, a surgeon in the operating theatre to interrogate patient-specific medical data sets rendered in three dimensions using high-performance computing. The hypothesis of this research is that the success rate of hepato-pancreatic surgical resections can be improved by replacing the light box with an interactive 3D representation of the medical data in the operating theatre.A laptop serves as the client computer and an easy-to-use interface has been developed for the surgeon to interact with and interrogate the patient data. To date, 16 patients have had 3D reconstructions of their DICOM data sets, including preoperative interrogation and planning of surgery.Interrogation of the 3D images live in theatre and comparison with the surgeons' operative findings (including intraoperative ultrasound) led to the operation being abandoned in 25% of cases, adoption of an alternative surgical approach in 25% of cases, and helpful image guidance for successful resection in 50% of cases.The clinical value of the latest generation of scanners and digital imaging techniques cannot be realized unless appropriate dissemination of the images takes place. This project has succeeded in translating the image technology into a user-friendly form and delivers 3D reconstructions of patient-specific data to the "sharp end"-the surgeon undertaking the tumor resection in theatre, in a manner that allows interaction and interpretation. More time interrogating the 3D data sets preoperatively would help reduce the incidence of abandoned operations-this is part of the surgeons' learning curve. We have developed one of the first practical applications to benefit from remote visualization, and certainly the first medical visualization application of this kind.

We have designed a configurable virtual environment to train rugby ball passing skills. Seeking to validate the system’s ability to correctly aid training, two experiments were performed. Ten participants took part in ball passing activities, which were used to compare the combinations of different user positions relative to the physical screen, the use of stereoscopic presentation and the use of a floor screen to extend the field of view of the virtual scene. Conversely to what was expected, the results indicate that the participants did not respond well to simulated target distances, and only the users physical distance from the screen had an effect on the distance thrown.

Interventional Radiology procedures (e.g., angioplasty, embolization, stent graft placement) provide minimally invasive therapy to treat a wide range of conditions. These procedures involve the use of flexible tipped guidewires to advance diagnostic or therapeutic catheters into a patient's vascular or visceral anatomy. This paper presents a real-time physically based hybrid modeling approach to simulating guidewire insertions. The long, slender body of the guidewire shaft is simulated using nonlinear elastic Cosserat rods, and the shorter flexible tip composed of a straight, curved, or angled design is modeled using a more efficient generalized bending model. Therefore, the proposed approach efficiently computes intrinsic dynamic behaviors of guidewire interactions within vascular structures. The efficacy of the proposed method is demonstrated using detailed numerical simulations inside 3-D blood vessel structures derived from preprocedural volumetric data. A validation study compares positions of four physical guidewires deployed within a vascular phantom, with the co-ordinates of the corresponding simulated guidewires within a virtual model of the phantom. An optimization algorithm is also implemented to further improve the accuracy of the simulation. The presented simulation model is suitable for interactive virtual reality-based training and for treatment planning.

The original publication is available at www.springerlink.com; International audience; Purpose : We present here a simulator for interventional radiology focusing on percutaneous transhepatic cholangiography (PTC). This procedure consists of inserting a needle into the biliary tree using fluoroscopy for guidance. Methods : The requirements of the simulator have been driven by a task analysis. The three main components have been identified: the respiration, the real-time X-ray display (fluoroscopy) and the haptic rendering (sense of touch). The framework for modelling the respiratory motion is based on kinematics laws and on the Chainmail algorithm. The fluoroscopic simulation is performed on the graphic card and makes use of the Beer-Lambert law to compute the X-ray attenuation. Finally, the haptic rendering is integrated to the virtual environment and takes into account the soft-tissue reaction force feedback and maintenance of the initial direction of the needle during the insertion. Results : Five training scenarios have been created using patient-specific data. Each of these provides the user with variable breathing behaviour, fluoroscopic display tuneable to any device parameters and needle force feedback. Conclusions : A detailed task analysis has been used to design and build the PTC simulator described in this paper. The simulator includes real-time respiratory motion with two independent parameters (rib kinematics and diaphragm action), on-line fluoroscopy implemented on the Graphics Processing Unit and haptic feedback to feel the soft-tissue behaviour of the organs during the needle insertion.

Closed-form solutions for lowpass filtering of 3D digital geometry are presented. Conventional signal processing is difficult to apply since 3D digital geometry does not usually satisfy the prerequisites of regular sampling and global parameterisation. Representing digital geometry as a level set of a 3D scalar field fitted with Gaussians and polynomials, derived are closed-form solutions of convolution with Gaussian smoothing kernels and lowpass filtering without the pitfalls of other approaches are analytically achieved.

jgViz uses standard grid technologies and Chromium cluster graphics software to schedule the best available distributed graphics pipeline. Visualization of large data sets using computer graphics techniques has become a mainstream requirement for many scientists and engineers. However, achieving interactive performance when rendering a complex visualization often requires high-performance computing facilities. One solution is to exploit real-time graphics accelerators, which are used in the full range of computing devices from games consoles and set-top boxes to supercomputers and advanced training simulators. At the same time, the service infrastructure for distributed networks has produced the third generation of the connected world: the grid. jgViz, our Java-implemented grid visualization system, uses grid functionality to enable transparent access to reliable parallel graphics pipelines. Lightweight and highly portable, jgViz aims to be plug-and-play for the existing grid resource allocation mechanism

Convolutional radial basis function (RBF) networks are introduced for smoothing out irregularly sampled signals. The proposed technique involves training an RBF network and then convolving it with a Gaussian smoothing kernel in an analytical manner. Since the convolution results in an analytic form, the computation necessary for numerical convolution is avoided. Convolutional RBF networks need training only once, do not depend on any particular details of the training methods used, and different degrees of smoothing are immediately available.

Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients., {"references":["Bethel .W, Tierney. Brian, Lee. J, Gunter .D, Lau S (2000): Visapult\nUsing High-Speed WANs and Network Data Caches to Enable Remote\nand Distributed Visualization, 2000 IEEE.","Xiaoyu Zhang, Chandrajit Bajaj, William Blanke : 2001 Scalable\nIsosurface Visualization of Massive Datasets on COTS Clusters :\nProceedings of the IEEE 2001 symposium on parallel and large-data\nvisualization and graphics.","Engel K Sommer .O, Ernst C, Ertl T. (2000): Remote 3D Visualization\nusing Image- Streaming Techniques. 2000.","Brett Beeson1,2, Mark Dwyer1, David 2005 : Server-side Visualization\nof Massive Datasets Thompson3 Proceedings of the First International\nConference on e-Science and Grid Computing (e-Science-05).","Foster, C. Kesselman, Nick .K. M., Tuecke .S (2002): The Physiology of\nthe Grid: An Open Grid Services Architecture for Distributed Systems\nIntegration. Technical report, Globus, February 2002.","McCormick B. H., DeFanti T. A., Brown M. D. (1987), \"Visualization in\nScientific Computing\", Computer Graphics 21 1-14.","Haber, R.B. and McNabb, D.A. 1990. Visualization Idioms: A\nConceptual Model for Scientific Visualization Systems. In:\nVisualization in Scientific Computing, Shriver, B., Neilson, G.M., and\nRosenblum, L.J., Eds., IEEE Computer Society Press, 74-93.","Upson, C., Faulhaber, T., Kamins, D., Schlegel, D., Laidlaw, D.,\nVroom, J., Gurwitz, R. and van Dam, A. 1989. The Application\nVisualization System: a Computational Environment for Scientific\nVisualization, IEEE Computer Graphics and Applications 9, 4, 30- 42.","Will Schroeder, Ken Martin, and Bill Lorensen, The Visualization\nToolkit: An Object-Oriented Approach To 3D Graphics. Second Edition.\nPrentice Hall. Upper Saddle River, NJ. 1998.\n[10] SGI. SGI OpenGL VizServer 3.1. Data sheet, SGI, March 2003.\n[11] Walton, J.P.R.B. (2004). NAG-s IRIS Explorer. In: Visualization\nHandbook, Johnson, C.R. and Hansen, C.D., Eds., Academic Press (in\npress). Available at http://www.nag.co.uk/doc/TechRep/Pdf/tr2_03.pdf\n[12] Walker D. W. , Grimstead .I (2004): Resource aware visualization\nenvironment. http://www.wesc.ac.uk/projects/rave/.2004\n[13] Wood. J, Brodlie, K., J. Walton. (2003) gViz - visualization and\nsteering for the grid. In Proceedings of the UK All Hands Meeting 2003,\nhttp://www.nesc.ac.uk/events/ahm2003/AHMCD/pdf/030.pdf.,\nhttp://www.visualization.leeds.ac.uk/gViz.\n[14] Charters, S., Holliman, N.S. and Munro, M. 2003. Visualization in e-\nDemand: Grid Service Architecture for Stereoscopic Visualization,\nProceedings of UK e-Science Second All Hands Meeting.\n[15] Osborne .J, Wright .H, (2003) SuperVise: Using Grid Tools to Support\nVisualization. In Proceedings of the Fifth International Conference on\nParallel Processing and Applied Mathematics (PPAM 2003).\n[16] Mahovsky .J, Benedicenti. L (2003): Architecture for Java-Based Real-\nTime Distributed Visualization. IEEE Transactions on Visualization and\nComputer Graphics, 9(4):570 - 579, October December 2003.\n[17] Allen .G, Benger. W, Goodale. T, Hege H.-C, Lanfermann . G , Merzky .\nA, Radke. T , Seidel .E, Shalf .J (2000): The Cactus Code: A Problem\nSolving Environment for the Grid. In Proceedings of the Ninth\nInternational Symposium on High Performance Distributed Computing\n(HPDC-00), pages 253-262. IEEE, August 2000.\n[18] Engel K. et al.. (2000): Combining Local and Remote Visualization\nTechniques for Interactive Volume Rendering in Medical Applications.\n2000.\n[19] Lorensen, William and Harvey E. Cline. Marching Cubes: A High\nResolution 3D Surface Construction Algorithm. Computer Graphics\n(SIGGRAPH 87 Proceedings) 21(4) July 1987, p. 163-170)\nhttp://www.cs.duke.edu/education/courses/fall01/cps124/resources/p163\n-lorensen.pdf\n[20] Ade J. Fewings and Nigel W. John, \"Distributed Graphics Pipelines on\nthe Grid,\" IEEE Distributed Systems Online, vol. 8, no. 1, 2007, art. no.\n0701-o1001.\n[21] Dutra, Rodrigues, Giraldi, Schulze, \"Distributed Visualization Using\nVTK in Grid Environments,\" ccgrid, pp. 381-388, Seventh IEEE\nInternational Symposium on Cluster Computing and the Grid (CCGrid\n'07), 2007.\n[22] William J. Schroeder, Jonathan A. Zarge , William E. Lorensen,\nDecimation of triangle meshes, ACM SIGGRAPH Computer Graphics,\nv.26 n.2, p.65-70, July 1992.\n[23] Thomas Sandholm and Jarek Gawor. Globus Toolkit 3 Core - A Grid\nService Container Framework. Globus Toolkit 3 Core White Paper, July\n2003.\n[24] M. L. Massie, B. N. Chun, and D. E. Culler, The Ganglia Distributed\nMonitoring System: Design, Implementation, and Experience, Parallel\nComputing, Vol. 30, Issue 7, July, 2004.\n[25] Ian Bowman 2004 Performance Modeling for 3D Visualization in a\nHeterogeneous Computing Environment: available online\nhttp://vis.lbl.gov/Publications/2004/Bowman-PGV-LBNL-56977.pdf"]}