Enhancing direct volume visualisation using perceptual properties
Mueller, Daniel C., Maeder, Anthony J., & O'Shea, Peter J. (2005) Enhancing direct volume visualisation using perceptual properties. In Galloway, Robert L. & Cleary, Kevin R. (Eds.) SPIE Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display, 12th - 17th February, San Diego, California, USA.
Direct volume rendering (DVR) is a visualisation technique allowing users to create 2-D renditions from 3-D spatial datasets. This technique can assist medical users in both diagnosis and therapy planning. Currently users of such visualisation systems have limited means of selecting visualisation parameters to enhance important regions of interest (ROI). We propose a modification to 3-D texture-based volume rendering allowing users to visually enhance important regions, while retaining contextual information. Using a series of interleaved region slices, the algorithm assigns a different transfer function to the ROI and context. Knowledge about the human visual system is used to modify the two transfer functions creating "pop-out" effects. This approach is demonstrated using the perceptual characteristics of luminance and hue. The output of this research is the new ability for users to precisely control the highlighting of regions of interest and hence improve the visualisation process.
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|Item Type:||Conference Paper|
|Keywords:||volume rendering, visualisation, perception, region of interest, transfer function|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Graphics (080103)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
|Copyright Owner:||Copyright 2005 Society of Photo-Optical Instrumentation Engineers|
|Copyright Statement:||This paper was published in Proceedings of Medical Imaging: Visualization, Image-Guided Procedures and Display (5744) and is made available as an electronic print with permission of SPIE. One print or electronic may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication or any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.|
|Deposited On:||24 Jun 2005|
|Last Modified:||01 Sep 2014 10:07|
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