A new segmentation algorithm for measuring CBCT images of nasal airway: a pilot study.

ABSTRACT:

Background

Three-dimensional (3D) modeling of the nasal airway space is becoming increasingly important for assessment in breathing disorders. Processing cone beam computed tomography (CBCT) scans of this region is complicated, however, by the intricate anatomy of the sinuses compared to the simpler nasopharynx. A gold standard for these measures also is lacking. Previous work has shown that software programs can vary in accuracy and reproducibility outcomes of these measurements. This study reports the reproducibility and accuracy of an algorithm, airway segmentor (AS), designed for nasal airway space analysis using a 3D printed anthropomorphic nasal airway model.

Methods

To test reproducibility, two examiners independently used AS to edit and segment 10 nasal airway CBCT s

SUBMITTER: Zhang C 

PROVIDER: S-EPMC6354662 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature