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Human Brain Diffusion Tensor Imaging Visualization With Virtual Reality

[+] Author Affiliations
Bin Chen, John Moreland

Purdue University Calumet, Hammond, IN

Paper No. WINVR2010-3761, pp. 137-143; 7 pages
  • ASME 2010 World Conference on Innovative Virtual Reality
  • ASME 2010 World Conference on Innovative Virtual Reality
  • Ames, Iowa, USA, May 12–14, 2010
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4908-8 | eISBN: 978-0-7918-3869-3
  • Copyright © 2010 by ASME


Magnetic resonance diffusion tensor imaging (DTI) is sensitive to the anisotropic diffusion of water exerted by its macromolecular environment and has been shown useful in characterizing structures of ordered tissues such as the brain white matter, myocardium, and cartilage. The water diffusivity inside of biological tissues is characterized by the diffusion tensor, a rank-2 symmetrical 3×3 matrix, which consists of six independent variables. The diffusion tensor contains much information of diffusion anisotropy. However, it is difficult to perceive the characteristics of diffusion tensors by looking at the tensor elements even with the aid of traditional three dimensional visualization techniques. There is a need to fully explore the important characteristics of diffusion tensors in a straightforward and quantitative way. In this study, a virtual reality (VR) based MR DTI visualization with high resolution anatomical image segmentation and registration, ROI definition and neuronal white matter fiber tractography visualization and fMRI activation map integration is proposed. The VR application will utilize brain image visualization techniques including surface, volume, streamline and streamtube rendering, and use head tracking and wand for navigation and interaction, the application will allow the user to switch between different modalities and visualization techniques, as well making point and choose queries. The main purpose of the application is for basic research and clinical applications with quantitative and accurate measurements to depict the diffusivity or the degree of anisotropy derived from the diffusion tensor.

Copyright © 2010 by ASME



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