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dc.contributor.authorHermosilla, Pedroen_US
dc.contributor.authorBrecheisen, Ralphen_US
dc.contributor.authorVázquez, Pere-Pauen_US
dc.contributor.authorVilanova, Annaen_US
dc.contributor.editorIsabel Navazo and Gustavo Patowen_US
dc.description.abstractDiffuse Tensor Imaging (DTI) is an acquisition method based on Magnetic Resonance (MR) that provides information on the white matter fiber pathways in the living human brain. Such knowledge is crucial for understanding the way different parts of the brain work and how they interact with each other. The reconstruction of fiber tracts, however, depends on a number of parameters that introduce a degree of uncertainty in the data. Together with the parameter setting, other elements such as noise, motion, partial volume effects, or image artifacts increase the uncertainty. Therefore, fiber tracking algorithms may produce misleading results. Visualizing such uncertainty is important to avoid taking wrong decisions in medical environments. In this paper we present a set of techniques that provide a better understanding on the visualization of brain fibers by means of textures, silhouettes, ambient occlusion, and animation.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectPicture/Image Generationen_US
dc.subjectDisplay Algorithmsen_US
dc.titleUncertainty Visualization of Brain Fibersen_US
dc.description.seriesinformationSpanish Computer Graphics Conferenceen_US

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  • CEIG12
    ISBN 978-3-905673-92-0

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