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Visualization Symposium, IEEE Pacific (2012)
Songdo, Korea (South)
Feb. 28, 2012 to Mar. 2, 2012
ISBN: 978-1-4673-0863-2
pp: 193-200
Yaniv Gur , SCI Institute, USA
Fangxiang Jiao , SCI Institute, USA
Chris R. Johnson , SCI Institute, USA
Jeff M. Phillips , University of Utah, USA
In this paper, we propose a new and accurate technique for uncertainty analysis and uncertainty visualization based on fiber orientation distribution function (ODF) glyphs, associated with high angular resolution diffusion imaging (HARDI). Our visualization applies volume rendering techniques to an ensemble of 3D ODF glyphs, which we call SIP functions of diffusion shapes, to capture their variability due to underlying uncertainty. This rendering elucidates the complex heteroscedastic structural variation in these shapes. Furthermore, we quantify the extent of this variation by measuring the fraction of the volume of these shapes, which is consistent across all noise levels, the certain volume ratio. Our uncertainty analysis and visualization framework is then applied to synthetic data, as well as to HARDI human-brain data, to study the impact of various image acquisition parameters and background noise levels on the diffusion shapes.
Yaniv Gur, Fangxiang Jiao, Chris R. Johnson, Jeff M. Phillips, "Uncertainty visualization in HARDI based on ensembles of ODFs", Visualization Symposium, IEEE Pacific, vol. 00, no. , pp. 193-200, 2012, doi:10.1109/PacificVis.2012.6183591
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