Book chapter
A New Method for Spherical Object Detection and Its Application to Computer Aided Detection of Pulmonary Nodules in CT Images
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007, pp.842-849
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2007
DOI: 10.1007/978-3-540-75757-3_102
PMID: 18051137
Abstract
A novel method called local shape controlled voting has been developed for spherical object detection in 3D voxel images. By introducing local shape properties into the voting procedure of normal overlap, the proposed method improves the capability of differentiating spherical objects from other structures, as the normal overlap technique only measures the ‘density’ of normal overlapping, while how the normals are distributed in 3D is not discovered. The proposed method was applied to computer aided detection of 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
- A New Method for Spherical Object Detection and Its Application to Computer Aided Detection of Pulmonary Nodules in 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
- Book chapter
- Publication Details
- Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007, pp.842-849
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-540-75757-3_102
- PMID
- 18051137
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Language
- English
- Date published
- 2007
- 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
- 9984186595402771
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