EuroVisShort2017

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https://diglib.eg.org/handle/10.2312/2631438

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Browsing EuroVisShort2017 by Subject "centered computing"

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    Interactive Level-of-Detail Visualization of 3D-Polarized Light Imaging Data Using Spherical Harmonics
    (The Eurographics Association, 2017) Hänel, Claudia; Demiralp, Ali C.; Axer, Markus; Grässel, David; Hentschel, Bernd; Kuhlen, Torsten W.; Barbora Kozlikova and Tobias Schreck and Thomas Wischgoll
    3D-Polarized Light Imaging (3D-PLI) provides data that enables an exploration of brain fibers at very high resolution. However, the visualization poses several challenges. Beside the huge data set sizes, users have to visually perceive the pure amount of information which might be, among other aspects, inhibited for inner structures because of occlusion by outer layers of the brain. We propose a clustering of fiber directions by means of spherical harmonics using a level-of-detail structure by which the user can interactively choose a clustering degree according to the zoom level or details required. Furthermore, the clustering method can be used for the automatic grouping of similar spherical harmonics automatically into one representative. An optional overlay with a direct vector visualization of the 3D-PLI data provides a better anatomical context.
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    Molecular Visualization of Computational Biology Data: A Survey of Surveys
    (The Eurographics Association, 2017) Alharbi, Naif; Alharbi, Mohammad; Martinez, Xavier; Krone, Michael; Rose, Alexander S.; Baaden, Marc; Laramee, Robert S.; Chavent, Matthieu; Barbora Kozlikova and Tobias Schreck and Thomas Wischgoll
    Visualizations for computational biology have been developing for over 50 years. With recent advances in both computational biology and computer graphics techniques, these fields have witnessed rapid technological advances in the last decade. Thus, coping with the large number of scientific articles from both fields is a challenging task. Furthermore, there remains a gap between the two communities of visualization and computational biology, resulting in additional challenges to bridge the divide. A team of computational biology and visualization scientists attempts to address these challenges by presenting unified state-of-the-art reviews from both communities. We apply a variety of data-driven analysis to highlight links or differences between studies from both communities. This approach facilitates the identification of present and future challenges in visualizing and analyzing computational biology data. It offers a distinctive step forward in managing the literature on visualization of molecular dynamics and related simulation approaches.