Automatic cross-sectioning based on topological volume skeletonization

Yuki Mori, Shigeo Takahashi, Takeo Igarashi, Yuriko Takeshima, Issei Fujishiro

Research output: Contribution to journalConference article

5 Citations (Scopus)

Abstract

Cross-sectioning is a popular method for visualizing the complicated inner structures of three-dimensional volume datasets. However, the process is usually manual, meaning that a user must manually specify the cross-section's location using a repeated trial-and-error process. To find the best cross-sections, this method requires that a user is knowledgeable and experienced. This paper proposes a method for automatically generating characteristic cross-sections from a given volume dataset. The application of a volume skeleton tree (VST), which is a graph that delineates the topological structure of a three-dimensional volume, facilitates the automated generation of cross-sections giving good representations of the topological characteristics of a dataset. The feasibility of the proposed method is demonstrated using several examples.

Original languageEnglish
Pages (from-to)175-184
Number of pages10
JournalLecture Notes in Computer Science
Volume3638
Publication statusPublished - 2005 Oct 27
Externally publishedYes
Event5th International Symposium on Smart Graphics, SG 2005 - Frauenworth Cloister, Germany
Duration: 2005 Aug 222005 Aug 24

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Mori, Y., Takahashi, S., Igarashi, T., Takeshima, Y., & Fujishiro, I. (2005). Automatic cross-sectioning based on topological volume skeletonization. Lecture Notes in Computer Science, 3638, 175-184.