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Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 11 — Nov. 1, 2013
  • pp: 2383–2395

Automated quantification of lung structures from optical coherence tomography images

Alex M. Pagnozzi, Rodney W. Kirk, Brendan F. Kennedy, David D. Sampson, and Robert A. McLaughlin  »View Author Affiliations

Biomedical Optics Express, Vol. 4, Issue 11, pp. 2383-2395 (2013)

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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.

© 2013 Optical Society of America

OCIS Codes
(100.0100) Image processing : Image processing
(100.2960) Image processing : Image analysis
(110.4500) Imaging systems : Optical coherence tomography

ToC Category:
Image Processing

Original Manuscript: July 22, 2013
Revised Manuscript: September 24, 2013
Manuscript Accepted: September 26, 2013
Published: October 9, 2013

Alex M. Pagnozzi, Rodney W. Kirk, Brendan F. Kennedy, David D. Sampson, and Robert A. McLaughlin, "Automated quantification of lung structures from optical coherence tomography images," Biomed. Opt. Express 4, 2383-2395 (2013)

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