Case study: interacting with volumetric medical datasets in networked CAVE environments

Ali H. Al-khalifah; Robin Woff; Vassil N. Alexandrov; Dave J. Roberts

doi:10.1117/12.587633

11 March 2005 Case study: interacting with volumetric medical datasets in networked CAVE environments

Ali H. Al-khalifah, Robin Woff, Vassil N. Alexandrov, Dave J. Roberts

Proceedings Volume 5669, Visualization and Data Analysis 2005; (2005) https://doi.org/10.1117/12.587633
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

Virtual Reality (VR) is widely used in visualizing medical datasets. This interest has emerged due to the usefulness of its techniques and features. Such features include immersion, collaboration, and interactivity. In a medical visualization context, immersion is important, because it allows users to interact directly and closely with detailed structures in medical datasets. Collaboration on the other hand is beneficial, because it gives medical practitioners the chance to share their expertise and offer feedback and advice in a more effective and intuitive approach. Interactivity is crucial in medical visualization and simulation systems, because responsive and instantaneous actions are key attributes in applications, such as surgical simulations. In this paper we present a case study that investigates the use of VR in a collaborative networked CAVE environment from a medical volumetric visualization perspective. The study will present a networked CAVE application, which has been built to visualize and interact with volumetric datasets. We will summarize the advantages of such an application and the potential benefits of our system. We also will describe the aspects related to this application area and the relevant issues of such implementations.

Citation Download Citation

Ali H. Al-khalifah, Robin Woff, Vassil N. Alexandrov, and Dave J. Roberts "Case study: interacting with volumetric medical datasets in networked CAVE environments", Proc. SPIE 5669, Visualization and Data Analysis 2005, (11 March 2005); https://doi.org/10.1117/12.587633

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