Journal article
Rule-based detection of intrathoracic airway trees
IEEE transactions on medical imaging, Vol.15(3), pp.314-326
1996
DOI: 10.1109/42.500140
PMID: 18215912
Abstract
New sensitive and reliable methods for assessing alterations in regional lung structure and function are critically important for the investigation and treatment of pulmonary diseases. Accurate identification of the airway tree will provide an assessment of airway structure and will provide a means by which multiple volumetric images of the lung at the same lung volume over time can be used to assess regional parenchymal changes. The authors describe a novel rule-based method for the segmentation of airway trees from three-dimensional (3-D) sets of computed tomography (CT) images, and its validation. The presented method takes advantage of a priori anatomical knowledge about pulmonary airway and vascular trees and their interrelationships. The method is based on a combination of 3-D seeded region growing that is used to identify large airways, rule-based two-dimensional (2-D) segmentation of individual CT slices to identify probable locations of smaller diameter airways, and merging of airway regions across the 3-D set of slices resulting in a tree-like airway structure. The method was validated in 40 3-mm-thick CT sections from five data sets of canine lungs scanned via electron beam CT in vivo with lung volume held at a constant pressure. The method's performance was compared with that of the conventional 3-D region growing method. The method substantially outperformed an existing conventional approach to airway tree detection.
Details
- Title: Subtitle
- Rule-based detection of intrathoracic airway trees
- Creators
- M SONKA - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, United StatesW PARK - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, United StatesE. A HOFFMAN - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, United States
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.15(3), pp.314-326
- DOI
- 10.1109/42.500140
- PMID
- 18215912
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers; New York, NY
- Language
- English
- Date published
- 1996
- 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
- 9984047891502771
Metrics
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