• DocumentCode
    1502657
  • Title

    Visualizing and segmenting large volumetric data sets

  • Author

    Senger, Steven

  • Author_Institution
    Wisconsin Univ., La Crosse, WI, USA
  • Volume
    19
  • Issue
    3
  • fYear
    1999
  • Firstpage
    32
  • Lastpage
    37
  • Abstract
    Current systems for segmenting and visualizing volumetric data sets characteristically require the user to possess a technical sophistication in volume visualization techniques, thus restricting the potential audience of users. As large volumetric data sets become more common, segmentation and visualization tools need to deemphasize the technical aspects of visualization and let users exploit their content knowledge of the data set. This proves especially critical in an educational setting. In anatomical education, data sets such as the Visible Human Project provide significant learning opportunities, but students must have tools that let them apply, refine, and build on their anatomical knowledge without technical obstacles. I describe a software environment that uses immersive virtual reality technology to let users immediately apply their expert knowledge to exploring and visualizing volumetric data sets
  • Keywords
    biomedical education; computer aided instruction; data visualisation; image segmentation; medical image processing; virtual reality; Visible Human Project; anatomical education; educational setting; immersive virtual reality technology; large volumetric data set segmentation; large volumetric data set visualization; learning opportunities; software environment; volume visualization techniques; Biomedical imaging; Data mining; Data visualization; Graphics; Humans; Image segmentation; Lighting; Liquid crystal displays; Solid modeling; Space technology;
  • fLanguage
    English
  • Journal_Title
    Computer Graphics and Applications, IEEE
  • Publisher
    ieee
  • ISSN
    0272-1716
  • Type

    jour

  • DOI
    10.1109/38.761546
  • Filename
    761546