Automatic cross-sectioning based on topological volume skeletonization

Authors:
Yuki Mori;Shigeo Takahashi;Takeo Igarashi;Yuriko Takeshima;Issei Fujishiro
Affiliations:
Department of Computer Science, The University of Tokyo, Tokyo, Japan;Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan;Department of Computer Science, The University of Tokyo / PRESTO, Tokyo, Japan;Institute of Fluid Science, Tohoku University, Sendai, Japan;Institute of Fluid Science, Tohoku University, Sendai, Japan
Venue:
SG'05 Proceedings of the 5th international conference on Smart Graphics
Year:
2005

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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.