Automated quantification of lung structures from optical coherence tomography images

Pagnozzi A.M., Kirk R.W., Kennedy B.F., Sampson D.D. and McLaughlin R.A. (2013) Automated quantification of lung structures from optical coherence tomography images. Biomedical Optics Express, 4 11: 2383-2395. doi:10.1364/BOE.4.002383


Author Pagnozzi A.M.
Kirk R.W.
Kennedy B.F.
Sampson D.D.
McLaughlin R.A.
Title Automated quantification of lung structures from optical coherence tomography images
Journal name Biomedical Optics Express   Check publisher's open access policy
ISSN 2156-7085
Publication date 2013-11-01
Sub-type Article (original research)
DOI 10.1364/BOE.4.002383
Open Access Status DOI
Volume 4
Issue 11
Start page 2383
End page 2395
Total pages 13
Place of publication Washington, DC United States
Publisher Optical Society of America
Collection year 2014
Language eng
Subject 3107 Atomic and Molecular Physics, and Optics
1305 Biotechnology
Formatted abstract
Characterization of the size of lung structures can aid in the assessment of a range of respiratory diseases. In this paper, we present a fully automated segmentation and quantification algorithm for the delineation of large numbers of lung structures in optical coherence tomography images, and the characterization of their size using the stereological measure of median chord length. We demonstrate this algorithm on scans acquired with OCT needle probes in fresh, ex vivo tissues from two healthy animal models: pig and rat. Automatically computed estimates of lung structure size were validated against manual measures. In addition, we present 3D visualizations of the lung structures using the segmentation calculated for each data set. This method has the potential to provide an in vivo indicator of structural remodeling caused by a range of respiratory diseases, including chronic obstructive pulmonary disease and pulmonary fibrosis.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
School of Medicine Publications
 
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