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Proceedings Paper

Feature extraction, analysis, and 3D visualization of local lung regions in volumetric CT images
Author(s): Andrzej Delegacz; Shih-Chung Benedict Lo; Matthew T. Freedman; Seong Ki Mun
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Paper Abstract

The purpose of the work was to develop image functions for volumetric segmentation, feature extraction, and enhanced 3D visualization of local regions using CT datasets of human lungs. The system is aimed to assist the radiologist in the analysis of lung nodules. Volumetric datasets consisting of 30-50 thoracic helical low-dose CT slices were used in the study. The 3D topological characteristics of local structures including bronchi, blood vessels, and nodules were computed and evaluated. When a location of a region of interest is identified, the computer would automatically compute size, surface of the area, and normalized shape index of the suspected lesion. The developed system can also allow the user to perform interactive operation for evaluation of lung regions and structures through a user- friendly interface. These functions provide the user with a powerful tool to observe and investigate clinically interesting regions through unconventional radiographic viewings and analyses. The developed functions can also be used to view and analyze patient's lung abnormalities in surgical planning applications. Additionally, we see the possibility of using the system as a teaching tool for correlating anatomy of lungs.

Paper Details

Date Published: 28 May 2001
PDF: 6 pages
Proc. SPIE 4319, Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures, (28 May 2001); doi: 10.1117/12.428121
Show Author Affiliations
Andrzej Delegacz, Georgetown Univ. Medical Ctr. and Catholic Univ. of America (United States)
Shih-Chung Benedict Lo, Georgetown Univ. Medical Ctr. (United States)
Matthew T. Freedman, Georgetown Univ. Medical Ctr. (United States)
Seong Ki Mun, Georgetown Univ. Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 4319:
Medical Imaging 2001: Visualization, Display, and Image-Guided Procedures
Seong Ki Mun, Editor(s)

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