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Proceedings Paper

Automated segmentation of lung airway wall area measurements from bronchoscopic optical coherence tomography imaging
Author(s): Mohammadreza Heydarian; Stephen Choy; Andrew Wheatley; David McCormack; Harvey O. Coxson; Stephen Lam; Grace Parraga
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Paper Abstract

Chronic Obstructive Pulmonary Disease (COPD) affects almost 600 million people and is currently the fourth leading cause of death worldwide. COPD is an umbrella term for respiratory symptoms that accompany destruction of the lung parenchyma and/or remodeling of the airway wall, the sum of which result in decreased expiratory flow, dyspnea and gas trapping. Currently, x-ray computed tomography (CT) is the main clinical method used for COPD imaging, providing excellent spatial resolution for quantitative tissue measurements although dose limitations and the fundamental spatial resolution of CT limit the measurement of airway dimensions beyond the 5th generation. To address this limitation, we are piloting the use of bronchoscopic Optical Coherence Tomography (OCT), by exploiting its superior spatial resolution of 5-15 micrometers for in vivo airway imaging. Currently, only manual segmentation of OCT airway lumen and wall have been reported but manual methods are time consuming and prone to observer variability. To expand the utility of bronchoscopic OCT, automatic and robust measurement methods are required. Therefore, our objective was to develop a fully automated method for segmenting OCT airway wall dimensions and here we explore several different methods of image-regeneration, voxel clustering and post-processing. Our resultant automated method used K-means or Fuzzy c-means to cluster pixel intensity and then a series of algorithms (i.e. cluster selection, artifact removal, de-noising) was applied to process the clustering results and segment airway wall dimensions. This approach provides a way to automatically and rapidly segment and reproducibly measure airway lumen and wall area.

Paper Details

Date Published: 9 March 2011
PDF: 9 pages
Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 79651M (9 March 2011); doi: 10.1117/12.878194
Show Author Affiliations
Mohammadreza Heydarian, Robarts Research Institute (Canada)
Stephen Choy, Robarts Research Institute (Canada)
Andrew Wheatley, Robarts Research Institute (Canada)
David McCormack, The Univ. of Western Ontario (Canada)
Harvey O. Coxson, Vancouver General Hospital (Canada)
Univ. of British Colombia (Canada)
Stephen Lam, The Univ. of British Colombia (Canada)
British Columbia Cancer Agency (Canada)
Grace Parraga, Robarts Research Institute (Canada)

Published in SPIE Proceedings Vol. 7965:
Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging
John B. Weaver; Robert C. Molthen, Editor(s)

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