Paper
24 April 2002 Development and validation of human airway analysis algorithm using multidetector row CT
Yasutaka Nakano, Kenneth P. Whittall, Steve E. Kalloger, Harvey O. Coxson, Julia Flint, Peter D. Pare, John C. English
Author Affiliations +
Abstract
There is currently no accurate method to measure airway dimensions on multidetector row computed tomography (multi-slice CT). We developed CT image analysis software to measure airway lumenal area (Ai) and airway wall area (Aaw) and compared these with quantitative morphology of excised human lungs as the gold standard. Airways identified on the CT images (1.25 mm collimation) were matched to airways identified on the lung's cut surface and Ai and Aaw were measured using custom software. The measured morphological airway lumen ranged from 1.0 to 6.4 mm in diameter. Airway dimensions obtained from CT data correlated with morphologic measurements (r = 0.96 for Ai and r = 0.91 for Aaw). However the CT systematically underestimated Ai and overestimated Aaw; average error (100 x (CT-morphology) / morphology) was -55% for Ai and +90% for Aaw. We used the morphology data to correct the CT measurements and reduced the average error to +23% for Ai and +7% for Aaw. This algorithm can be used to assess the structure and function of human airways.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yasutaka Nakano, Kenneth P. Whittall, Steve E. Kalloger, Harvey O. Coxson, Julia Flint, Peter D. Pare, and John C. English "Development and validation of human airway analysis algorithm using multidetector row CT", Proc. SPIE 4683, Medical Imaging 2002: Physiology and Function from Multidimensional Images, (24 April 2002); https://doi.org/10.1117/12.463615
Lens.org Logo
CITATIONS
Cited by 73 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Computed tomography

Lung

Algorithm development

Evolutionary algorithms

Gold

Adaptive optics

Scanners

Back to Top