Title :
Visualizing and segmenting large volumetric data sets
Author_Institution :
Wisconsin Univ., La Crosse, WI, USA
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;
Journal_Title :
Computer Graphics and Applications, IEEE