Conference proceeding
Knowledge-based segmentation of intrathoracic airways from multidimensional high-resolution CT images
Proceedings of SPIE, Vol.2168(1), pp.73-85
Medical Imaging 1994: Physiology and Function from Multidimensional Images
05/01/1994
DOI: 10.1117/12.174425
Abstract
A critically important component in the development of new methods for treatment of pulmonary diseases is the development of sensitive techniques for assessing alterations in regional lung structure and function. We describe an automated method for segmentation of airway trees from 3-D sets of CT images. The method is based on a combination of conventional 3-D seeded region growing that is used to identify large airways, knowledge- based 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 preliminary validation of the method was done in eighty 3 mm thick CT sections from two 40 slice data sets of a canine thorax scanned with lungs held at 1.5 kPa and 2.5 kPa. The method's performance was compared with that of the conventional 3-D region growing method. The knowledge-based approach to identification of potential airways in individual image slices substantially outperforms the conventional method and promises to be applicable to in vivo pulmonary CT images.
Details
- Title: Subtitle
- Knowledge-based segmentation of intrathoracic airways from multidimensional high-resolution CT images
- Creators
- Milan Sonka - University of IowaGopal Sundaramoorthy - University of IowaEric A Hoffman - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings of SPIE, Vol.2168(1), pp.73-85
- Conference
- Medical Imaging 1994: Physiology and Function from Multidimensional Images
- DOI
- 10.1117/12.174425
- ISSN
- 0277-786X
- eISSN
- 1996-756X
- Language
- English
- Date published
- 05/01/1994
- 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
- 9984186600902771
Metrics
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