VisualFlatter - Visual Analysis of Distortions in the Projection of Biomedical Structures

Information

• Publication Type: Journal Paper with Conference Talk
• Workgroup(s)/Project(s):
  • Visualization Group
• Date: September 2018
• Journal: Eurographics Proceedings
• Lecturer: Renata Raidou
• Event: Eurographics Workshop on Visual Computing for Biology and Medicine (2018)
• Call for Papers: Call for Paper
• Conference date: 2018

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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BibTeX

@article{raidou2018visualflatter,
  title =      "VisualFlatter - Visual Analysis of Distortions in the
               Projection of Biomedical Structures",
  author =     "Nicolas Grossmann and Thomas K\"{o}ppel and Eduard
               Gr\"{o}ller and Renata Raidou",
  year =       "2018",
  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.",
  month =      sep,
  journal =    "Eurographics Proceedings",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2018/raidou2018visualflatter/",
}