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Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation
November/December 2007 (vol. 13 no. 6)
pp. 1648-1655
ASCII Text
x 
 
Claes Lundström, Patric Ljung, Anders Persson, Anders Ynnerman, "Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1648-1655, November/December, 2007.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2007.70608,
author = {Claes Lundström and Patric Ljung and Anders Persson and Anders Ynnerman},
title = {Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {13},
number = {6},
issn = {1077-2626},
year = {2007},
pages = {1648-1655},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2007.70608},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation
IS - 6
SN - 1077-2626
SP1648
EP1655
EPD - 1648-1655
A1 - Claes Lundström,
A1 - Patric Ljung,
A1 - Anders Persson,
A1 - Anders Ynnerman,
PY - 2007
KW - Uncertainty
KW - probability
KW - medical visualization
KW - volume rendering
KW - transfer function
VL - 13
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Direct Volume Rendering has proved to be an effective visualization method for medical data sets and has reached wide-spread clinical use. The diagnostic exploration, in essence, corresponds to a tissue classification task, which is often complex and time-consuming. Moreover, a major problem is the lack of information on the uncertainty of the classification, which can have dramatic consequences for the diagnosis. In this paper this problem is addressed by proposing animation methods to convey uncertainty in the rendering. The foundation is a probabilistic Transfer Function model which allows for direct user interaction with the classification. The rendering is animated by sampling the probability domain over time, which results in varying appearance for uncertain regions. A particularly promising application of this technique is a “sensitivity lens” applied to focus regions in the data set. The methods have been evaluated by radiologists in a study simulating the clinical task of stenosis assessment, in which the animation technique is shown to outperform traditional rendering in terms of assessment accuracy.

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Index Terms:
Uncertainty, probability, medical visualization, volume rendering, transfer function
Citation:
Claes Lundström, Patric Ljung, Anders Persson, Anders Ynnerman, "Uncertainty Visualization in Medical Volume Rendering Using Probabilistic Animation," IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 6, pp. 1648-1655, Nov.-Dec. 2007, doi:10.1109/TVCG.2007.70608
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