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Proceedings Paper

Intrathoracic airway wall detection using graph search and scanner PSF information
Author(s): Joseph M. Reinhardt; Wonkyu Park; Eric A. Hoffman; Milan Sonka
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Paper Abstract

Measurements of the in vivo bronchial tree can be used to assess regional airway physiology. High-resolution CT (HRCT) provides detailed images of the lungs and has been used to evaluate bronchial airway geometry. Such measurements have been sued to assess diseases affecting the airways, such as asthma and cystic fibrosis, to measure airway response to external stimuli, and to evaluate the mechanics of airway collapse in sleep apnea. To routinely use CT imaging in a clinical setting to evaluate the in vivo airway tree, there is a need for an objective, automatic technique for identifying the airway tree in the CT images and measuring airway geometry parameters. Manual or semi-automatic segmentation and measurement of the airway tree from a 3D data set may require several man-hours of work, and the manual approaches suffer from inter-observer and intra- observer variabilities. This paper describes a method for automatic airway tree analysis that combines accurate airway wall location estimation with a technique for optimal airway border smoothing. A fuzzy logic, rule-based system is used to identify the branches of the 3D airway tree in thin-slice HRCT images. Raycasting is combined with a model-based parameter estimation technique to identify the approximate inner and outer airway wall borders in 2D cross-sections through the image data set. Finally, a 2D graph search is used to optimize the estimated airway wall locations and obtain accurate airway borders. We demonstrate this technique using CT images of a plexiglass tube phantom.

Paper Details

Date Published: 9 May 1997
PDF: 9 pages
Proc. SPIE 3033, Medical Imaging 1997: Physiology and Function from Multidimensional Images, (9 May 1997); doi: 10.1117/12.274033
Show Author Affiliations
Joseph M. Reinhardt, Univ. of Iowa College of Medicine (United States)
Wonkyu Park, Univ. of Iowa and Korea Advanced Institute of Science and Technology (United States)
Eric A. Hoffman, Univ. of Iowa College of Medicine (United States)
Milan Sonka, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 3033:
Medical Imaging 1997: Physiology and Function from Multidimensional Images
Eric A. Hoffman, Editor(s)

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