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Proceedings Paper

Extracting alveolar structure of human lung tissue specimens based on surface skeleton representation from 3D micro-CT images
Author(s): Hiroyuki Ishimori; Yoshiki Kawata; Noboru Niki; Yoshihiro Nakaya; Hironobu Ohmatsu; Eisuke Matsui; Masashi Fujii; Noriyuki Moriyama
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Paper Abstract

We have developed a Micro CT system for understanding lung function at a high resolution of the micrometer order (up to 5µm in spatial resolution). Micro CT system enables the removal specimen of lungs to be observed at micro level, has expected a big contribution for micro internal organs morphology and the image diagnosis study. In this research, we develop system to visualize lung microstructures in three dimensions from micro CT images and analyze them. They characterize in that high CT value of the noise area is, and the difficulty of only using threshold processing to extract the alveolar wall of micro CT images. Thus, we are developing a method of extracting the alveolar wall with surface thinning algorithm. In this report, we propose the method which reduces the excessive degeneracy of figure which caused by surface thinning process. And, we apply this algorithm to the micro CT image of the actual pulmonary specimen. It is shown that the extraction of the alveolus wall becomes possible in the high precision.

Paper Details

Date Published: 30 March 2007
PDF: 9 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65143O (30 March 2007); doi: 10.1117/12.709434
Show Author Affiliations
Hiroyuki Ishimori, Univ. of Tokushima (Japan)
Yoshiki Kawata, Univ. of Tokushima (Japan)
Noboru Niki, Univ. of Tokushima (Japan)
Yoshihiro Nakaya, Shizuoka Cancer Ctr. (Japan)
Hironobu Ohmatsu, National Cancer Ctr. Hospital East (Japan)
Eisuke Matsui, Gifu Research Institute for Enviromental Medicine (Japan)
Masashi Fujii, Toshiba Corp. (Japan)
Noriyuki Moriyama, National Cancer Ctr. Research Ctr. for Cancer Prevention and Screening (Japan)

Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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