Conference proceeding
Computerized detection of pulmonary nodules using a combination of 3D global and local shape information based on helical CT images
Proceedings of SPIE, Vol.6144(1), pp.61441V-61441V-10
Medical Imaging 2006: Image Processing
03/02/2006
DOI: 10.1117/12.654285
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.
Details
- Title: Subtitle
- Computerized detection of pulmonary nodules using a combination of 3D global and local shape information based on helical CT images
- Creators
- Xiangwei Zhang - University of IowaJonathan Stockel - Medical SolutionsMatthias Wolf - Medical SolutionsPascal Cathier - Medical SolutionsGeoffrey McLennan - University of IowaEric A Hoffman - University of IowaMilan Sonka - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.6144(1), pp.61441V-61441V-10
- Conference
- Medical Imaging 2006: Image Processing
- DOI
- 10.1117/12.654285
- ISSN
- 0277-786X
- Language
- English
- Date published
- 03/02/2006
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Internal Medicine; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186705402771
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