Grossmann, N., Köppel, T., Gröller, E., & Raidou, R. (2018). VisualFlatter - Visual Analysis of Distortions in the Projection of Biomedical Structures. In A. Puig, T. Schultz, A. Vilanova, I. Hotz, B. Kozlikova, & P.-P. Vázquez (Eds.), Eurographics Proceedings. Eurographics. https://doi.org/10.2312/vcbm.20181242
Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)
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Event date:
1-Jan-2018
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Event place:
Chester, United Kingdom of Great Britain and Northern Ireland (the)
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Number of Pages:
1
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Publisher:
Eurographics
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Publisher:
The Eurographics Association
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Peer reviewed:
Yes
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Abstract:
Projections of complex anatomical or biological structures from 3D to 2D are often used by visualization and domain experts to facilitate inspection and understanding. Representing complex structures, such as organs or molecules, in a simpler 2D way often requires less interaction, while enabling comparability. However, the most commonly employed projection methods introduce size or shape distortions, in the resulting 2D representations. While simple projections display known distortion patterns, more complex projection algorithms are not easily predictable.We propose the VisualFlatter, a visual analysis tool that enables visualization and domain experts to explore and analyze projection-induced distortions, in a structured way. Our tool provides a way to identify projected regions with semantically relevant distortions and allows users to comparatively analyze distortion outcomes, either from alternative projection methods or due to different setups through the projection pipeline. The user is given the ability to improve the initial projection configuration, after comparing different setups. We demonstrate the functionality of our tool using four scenarios of 3D to 2D projections, conducted with the help of domain or visualization experts working on different application fields. We also performed a wider evaluation with 13 participants, familiar with projections, to assess the usability and functionality of the Visual Flatter.
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Research Areas:
Visual Computing and Human-Centered Technology: 100%