Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Upper airway detection and visualization from cone beam image slices

Upper airway detection and visualization from cone beam image slices This paper describes a method developed to assist in the detection and reconstruction of a three dimensional (3D) model of the human upper airway using cone beam computed tomography (CBCT) image slices and a 3D Gaussian smoothing kernel. The segmented and reconstructed volumetric airway is characterized by the corresponding three principal axes that are selected for viewing direction orientation via rotation and translation. These axes are derived using the 3D Principal Component Analysis (PCA) result of the rendered volume. To finely adjust the view and access airway, the major and minor axes of each slice are also computed using the two dimensional (2D) PCA in the respective planes. The exterior volume view is visualized in two modes, namely, a solid surface (volume details transparent to user) view and a nontransparent (volume detail accessible) view. This functionality provides an application driven use of the 3D airway in CBCT based anatomy studies. The extracted information may be useful as an imaging biomarker in the diagnostic assessment of patients with upper airway respiratory conditions such as obstructive sleep apnea, allergic rhinitis, and other related diseases; as well as planning orthopedic/orthodontic therapies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of X-Ray Science and Technology IOS Press

Upper airway detection and visualization from cone beam image slices

Loading next page...
 
/lp/ios-press/upper-airway-detection-and-visualization-from-cone-beam-image-slices-D0P3Q0MCNH

References (31)

Publisher
IOS Press
Copyright
Copyright © 2010 by IOS Press, Inc
ISSN
0895-3996
eISSN
1095-9114
DOI
10.3233/XST-2010-0248
pmid
20495240
Publisher site
See Article on Publisher Site

Abstract

This paper describes a method developed to assist in the detection and reconstruction of a three dimensional (3D) model of the human upper airway using cone beam computed tomography (CBCT) image slices and a 3D Gaussian smoothing kernel. The segmented and reconstructed volumetric airway is characterized by the corresponding three principal axes that are selected for viewing direction orientation via rotation and translation. These axes are derived using the 3D Principal Component Analysis (PCA) result of the rendered volume. To finely adjust the view and access airway, the major and minor axes of each slice are also computed using the two dimensional (2D) PCA in the respective planes. The exterior volume view is visualized in two modes, namely, a solid surface (volume details transparent to user) view and a nontransparent (volume detail accessible) view. This functionality provides an application driven use of the 3D airway in CBCT based anatomy studies. The extracted information may be useful as an imaging biomarker in the diagnostic assessment of patients with upper airway respiratory conditions such as obstructive sleep apnea, allergic rhinitis, and other related diseases; as well as planning orthopedic/orthodontic therapies.

Journal

Journal of X-Ray Science and TechnologyIOS Press

Published: Jan 1, 2010

There are no references for this article.