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Proceedings Paper

Quantitative analysis of airway abnormalities in CT
Author(s): Jens Petersen; Pechin Lo; Mads Nielsen; Goutham Edula; Haseem Ashraf; Asger Dirksen; Marleen de Bruijne
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Paper Abstract

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).

Paper Details

Date Published: 9 March 2010
PDF: 12 pages
Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76241S (9 March 2010); doi: 10.1117/12.843937
Show Author Affiliations
Jens Petersen, Univ. of Copenhagen (Denmark)
Pechin Lo, Univ. of Copenhagen (Denmark)
Mads Nielsen, Univ. of Copenhagen (Denmark)
Goutham Edula, AstraZeneca R&D Lund (Sweden)
Haseem Ashraf, Gentofte Hospital (Denmark)
Asger Dirksen, Gentofte Hospital (Denmark)
Marleen de Bruijne, Univ. of Copenhagen (Denmark)
Erasmus MC (Denmark)

Published in SPIE Proceedings Vol. 7624:
Medical Imaging 2010: Computer-Aided Diagnosis
Nico Karssemeijer; Ronald M. Summers, Editor(s)

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