Hierarchical Poisson-Disk Sampling for Fiber Stipples

dc.contributor.authorHlawitschka, Marioen_US
dc.contributor.authorGoldau, Mathiasen_US
dc.contributor.authorWiebel, Alexanderen_US
dc.contributor.authorHeine, Christianen_US
dc.contributor.authorScheuermann, Geriken_US
dc.contributor.editorL. Linsen and H. -C. Hege and B. Hamannen_US
dc.date.accessioned2014-02-01T16:09:57Z
dc.date.available2014-02-01T16:09:57Z
dc.date.issued2013en_US
dc.description.abstractTo understand neural tracts of the brain, neuroscientists use visualizations of diffusion data. Fiber stippling - a technique inspired by illustrations - accommodates probabilistic tracts, main diffusion direction, and anatomical context in the same slice image. It uses stratified sampling to place stipples, but this can result in overlaps and undersampled areas that distort the perception of tract probability. Moreover, when changing slices in an interactive setting, resampling leads to visual noise that distracts from real changes in the data. In this paper, we propose to use Poisson-disk samplings to ensure adequate pattern perception inside slices and a hierarchy of samplings to ensure coherence among slices. We also port the algorithm to the GPU to achieve interactive frame rates. Our modifications are appreciated by neuroscientists, who can now investigate white-matter structures more confidently.en_US
dc.description.seriesinformationVisualization in Medicine and Life Sciencesen_US
dc.identifier.isbn978-3-905674-52-1en_US
dc.identifier.urihttps://doi.org/10.2312/PE.VMLS.VMLS2013.019-023en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectPicture/Image Generationen_US
dc.subjectLine and curve generationen_US
dc.titleHierarchical Poisson-Disk Sampling for Fiber Stipplesen_US
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