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dc.contributor.authorSchultz, Thomasen_US
dc.contributor.authorSchlaffke, Laraen_US
dc.contributor.authorSchölkopf, Bernharden_US
dc.contributor.authorSchmidt-Wilcke, Tobiasen_US
dc.contributor.editorB. Preim, P. Rheingans, and H. Theiselen_US
dc.date.accessioned2015-02-28T15:30:26Z
dc.date.available2015-02-28T15:30:26Z
dc.date.issued2013en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.12099en_US
dc.description.abstractObtaining reproducible fiber direction estimates from diffusion MRI is crucial for successful fiber tracking. Modeling and visualizing the probability distribution of the inferred fiber directions is an important step in evaluating and comparing different acquisition schemes and fiber models. However, this distribution is usually strongly dominated by its main direction, which makes it difficult to examine when plotted naively. In this work, we propose a new visualization of the fiber probability distribution. It is based on embedding the probability measure into a particular reproducing kernel Hilbert space. This permits a decomposition into an embedded delta peak, representing the main direction, and a non-negative residual. They are then combined into a new glyph representation which visually enhances the residual, in order to highlight even subtle differences. Moreover, the magnitude of the delta peak component quantifies precision of the main fiber direction. We demonstrate that our new glyph provides a more detailed impression of the uncertainty than the current standard method, cones that contain 95% of the estimated directions. We use our new method to contribute to the validation of different ways of resampling the data (bootstrapping), and to visualize the differences between alternative acquisition schemes and models for high angular resolution diffusion imaging (HARDI).en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectG.3 [Probability and Statistics]en_US
dc.subjectDistribution functionsen_US
dc.subjectI.3.8 [Computer Graphics]en_US
dc.subjectApplicationsen_US
dc.titleHiFiVE: A Hilbert Space Embedding of Fiber Variability Estimates for Uncertainty Modeling and Visualizationen_US
dc.description.seriesinformationComputer Graphics Forumen_US


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