Conference proceeding
Validation of an enhanced knowledge-based method for segmentation and quantitative analysis of intrathoracic airway trees from three-dimensional CT images
Proceedings of SPIE, Vol.2433(1), pp.158-166
Medical Imaging 1995: Physiology and Function from Multidimensional Images
05/24/1995
DOI: 10.1117/12.209688
Abstract
Accurate assessment of airway physiology, evaluated in terms of geometric changes, is critically dependent upon the accurate imaging and image segmentation of the 3D airway tree structure. We have previously reported a knowledge-based method for 3D airway tree segmentation from high resolution CT (HRCT) images. Here we report a substantially improved version of our method. In the current implementation, the method consists of several stages. First, the lung borders are automatically determined in the 3D set of HRCT data. The primary airway tree is semi-automatically identified. In the next stage, potential airways are determined in individual CT slices using a rule- based system that uses contextual information and a priori knowledge about pulmonary anatomy. Using 3D connectivity properties of the pulmonary airway tree, the 3D tree is constructed from the set of adjacent slices. The method's performance and accuracy were assessed in five 3D HRCT canine images. Computer-identified airways matched 226/258 observer-defined airways (87.6%); the computer method failed to detect the airways in the remaining 32 locations. By visual assessment of rendered airway trees, the experienced observers judged the computer-detected airway trees as highly realistic.
Details
- Title: Subtitle
- Validation of an enhanced knowledge-based method for segmentation and quantitative analysis of intrathoracic airway trees from three-dimensional CT images
- Creators
- Milan Sonka - Univ. of Iowa (USA)Wonkyu Park - Univ. of Iowa (USA)Eric A Hoffman - Univ. of Iowa College of Medicine (USA)
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.2433(1), pp.158-166
- Conference
- Medical Imaging 1995: Physiology and Function from Multidimensional Images
- DOI
- 10.1117/12.209688
- ISSN
- 0277-786X
- Language
- English
- Date published
- 05/24/1995
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Injury Prevention Research Center; Internal Medicine; Ophthalmology and Visual Sciences
- Record Identifier
- 9984047984102771
Metrics
11 Record Views