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.
|ジャーナル||Journal of the Institute of Image Electronics Engineers of Japan|
|出版ステータス||Published - 2006|
ASJC Scopus subject areas
- コンピュータ サイエンス（その他）