Paper
29 March 2007 Quantification of airway morphometry: the effect of CT acquisition and reconstruction parameters
J. Ken Leader, Bin Zheng, Frank C. Sciurba, Harvey O Coxson, Carl R. Fuhrman, Jessica M. McMurray, Sang C. Park, Glenn S. Maitz, David Gur
Author Affiliations +
Abstract
This study measured the accuracy of our airway quantification scheme using phantoms airway under different CT protocols. Airway remodeling is associated with several thoracic diseases (e.g., chronic bronchitis, asthma, and bronchiectasis), and, therefore, quantification of airway remodeling may have wide clinical application. Our scheme assigns pixels partial membership in the airway wall and lumen based on the pixel's HU value, which is intended to account for partial volume averaging inherent in CT image reconstruction. Twenty-four phantom airways with an outer diameter from 2.6 to 14.0 mm and wall thicknesses from 0.5 to 2.0 mm were analyzed. The absolute differences between measurements supplied by the manufacture and computed from CT images acquired at 40 mAs and reconstructed at 1.25 mm thickness using GE's "soft" and "lung" reconstruction kernels for lumen area ranged from 1.4% to 49.3% and 0.4% to 33.0%, respectively, and for wall area ranged from 0.3% to 118.0% and 2.1 to 92.9%, respectively. Accuracy typically improved as the kernel's spatial frequency increased. Airways whose wall thickness was close to the pixels dimensions were challenging to quantify. The partial membership assignment of our airway quantification accurately computed airway morphometry across a range of phantom airway sizes.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Ken Leader, Bin Zheng, Frank C. Sciurba, Harvey O Coxson, Carl R. Fuhrman, Jessica M. McMurray, Sang C. Park, Glenn S. Maitz, and David Gur "Quantification of airway morphometry: the effect of CT acquisition and reconstruction parameters", Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 65111R (29 March 2007); https://doi.org/10.1117/12.709940
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Cited by 7 scholarly publications.
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KEYWORDS
Lung

Computed tomography

Image segmentation

Manufacturing

CT reconstruction

Tissues

Chronic obstructive pulmonary disease

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