Background: Understanding airflow through human airways is of importance in drug delivery and development of assisted breathing methods. In this work, we focus on development of a new method to obtain an averaged upper airway geometry from computed tomography (CT) scans of many individuals. This geometry can be used for air flow simulation. We examine the geometry resulting from a data set consisting of 26 airway scans. The methods used to achieve this include nasal cavity segmentation and a deformable template matching procedure.
Methods: The method uses CT scans of the nasal cavity of individuals to obtain a segmented mesh, and coronal cross-sections of this segmented mesh are taken. The cross-sections are processed to extract the nasal cavity, and then thinned ('skeletonized') representations of the airways are computed. A reference template is then deformed such that it lies on this thinned representation. The average of these deformations is used to obtain the average geometry. Our procedure tolerates a wider variety of nasal cavity geometries than earlier methods.
Results: To assess the averaging method, key landmark points on each of the input scans as well as the output average geometry are located and compared with one another, showing good agreement. In addition, the cross-sectional area (CSA) profile of the nasal cavities of the input scans and average geometry are also computed, showing that the CSA of the average model falls within the variation of the population.
Conclusions: The use of a deformable template method for aligning and averaging the nasal cavity provides an improved, detailed geometry that is unavailable without using deformation.
Keywords: Human airways; Image registration; Thin-plate splines.