A coupled surface graph cut algorithm for airway wall segmentation from Computed Tomography (CT) images
is presented. Using cost functions that highlight both inner and outer wall borders, the method combines the
search for both borders into one graph cut.
The proposed method is evaluated on 173 manually segmented images extracted from 15 different subjects
and shown to give accurate results, with 37% less errors than the Full Width at Half Maximum (FWHM)
algorithm and 62% less than a similar graph cut method without coupled surfaces. Common measures of airway
wall thickness such as the Interior Area (IA) and Wall Area percentage (WA%) was measured by the proposed
method on a total of 723 CT scans from a lung cancer screening study. These measures were significantly different
for participants with Chronic Obstructive Pulmonary Disease (COPD) compared to asymptomatic participants.
Furthermore, reproducibility was good as confirmed by repeat scans and the measures correlated well with the
outcomes of pulmonary function tests, demonstrating the use of the algorithm as a COPD diagnostic tool.
Additionally, a new measure of airway wall thickness is proposed, Normalized Wall Intensity Sum (NWIS).
NWIS is shown to correlate better with lung function test values and to be more reproducible than previous
measures IA, WA% and airway wall thickness at a lumen perimeter of 10 mm (PI10).
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.