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Proceedings Paper

Computerized detection of pulmonary nodules using a combination of 3D global and local shape information based on helical CT images
Author(s): Xiangwei Zhang; Jonathan Stockel; Matthias Wolf; Pascal Cathier; Geoffrey McLennan; Eric A. Hoffman; Milan Sonka M.D.
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Paper Abstract

A novel method called local shape controlled voting has been developed for spherical object detection in 3D voxel images. By combining local shape properties into the global tracking procedure of normal overlap, the proposed method solved the ambiguities of normal overlap between a small size sphere and a possible large size cylinder, as the normal overlap technique can only measures the 'density' of normal overlapping, while how the normal vectors are distributed in 3D is not discovered. The proposed method was applied to computer aided detection of small size pulmonary nodules based on helical CT images. Experiments showed that this method attained a better performance compared to the original normal overlap technique.

Paper Details

Date Published: 10 March 2006
PDF: 10 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61441V (10 March 2006); doi: 10.1117/12.654285
Show Author Affiliations
Xiangwei Zhang, Univ. of Iowa (United States)
Jonathan Stockel, Siemens Medical Solutions (United States)
Matthias Wolf, Siemens Medical Solutions (United States)
Pascal Cathier, Siemens Medical Solutions (United States)
Geoffrey McLennan, Univ. of Iowa (United States)
Eric A. Hoffman, Univ. of Iowa (United States)
Milan Sonka M.D., Univ. of Iowa (United States)

Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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