Abstract
Cross-sectioning is one of the most commonly used methods for visualizing the complicated inner structures of three-dimensional volume datasets. However, the method usually requires a tedious trial-and-error process by users and thus often fails in finding characteristic cross-sections that capture the underlying inner structures. This paper presents a method for automatically generating characteristic cross-sections from a given volume dataset. The application of a graph structure called volume skeleton tree (VST) allows us to automatically extract such characteristic cross-sections by delineating the topological structure of the given volume. The feasibility of the proposed method is demonstrated using simulated and measured volume datasets.
Original language | English |
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Pages (from-to) | 252-260 |
Number of pages | 9 |
Journal | Journal of the Institute of Image Electronics Engineers of Japan |
Volume | 35 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2006 |
Externally published | Yes |
Keywords
- topology analysis
- volume data mining
- volume visualization
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Electrical and Electronic Engineering