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Effect of Multiple Iso-surfaces in Depth Perception in Transparent Stereoscopic Visualizations

  • Daimon AoiEmail author
  • Kyoko Hasegawa
  • Liang Li
  • Yuichi Sakano
  • Satoshi Tanaka
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1094)

Abstract

With the development of imaging technologies, it has become easier to obtain three-dimensional data of the internal human body by Computed Tomography and Magnetic Resonance Imaging. Visualizing these data helps us to understand the complicated internal structure of the human body. Transparent stereoscopic visualization is a good way to visualize the internal body structure with depth information. However, the position and depth information often become unclear when three-dimensional data are rendered transparently. In this study, we examined how depth perception changes by overlaying multiple iso-surfaces on transparently rendered images for structural understanding and correct depth perception in transparent stereoscopic visualization. We tested two types of figures: rectangular and medical data. The experimental results showed that multiple iso-surfaces improved the accuracy of perceived depth. For both figures, it was effective when the opacity of the inner iso-surface was high and the distance between the inner iso-surface and the outer iso-surface was large. In addition, the effect was particularly high when the distance between the inner and the outer iso-surface was large and the size of the inner iso-surface was small.

Keywords

Transparent stereoscopic visualization Multiple iso-surfaces Depth perception Medical volumetric data 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Daimon Aoi
    • 1
    Email author
  • Kyoko Hasegawa
    • 2
  • Liang Li
    • 2
  • Yuichi Sakano
    • 3
    • 4
  • Satoshi Tanaka
    • 2
  1. 1.Graduate School of Information Science and EngineeringRitsumeikan UniversityKusatsuJapan
  2. 2.College of Information Science and EngineeringRitsumeikan UniversityKusatsuJapan
  3. 3.Center for Information and Neural Networks (CiNet) National Institute of Information and Communications TechnologyOsaka UniversitySuitaJapan
  4. 4.Graduate School of Frontier BiosciencesOsaka UniversitySuitaJapan

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