Semi-automated tabulation of the 3D topology and morphology of branching networks using CT: application to the airway tree.
Detailed information on biological branching networks (optical nerves, airways or blood vessels) is often required to improve the analysis of 3D medical imaging data. A semi-automated algorithm has been developed to obtain the full 3D topology and dimensions (direction cosine, length, diameter, branching and gravity angles) of branching networks using their CT images. It has been tested using CT images of a simple Perspex branching network and applied to the CT images of a human cast of the airway tree. The morphology and topology of the computer derived network were compared with the manually measured dimensions. Good agreement was found. The airways dimensions also compared well with previous values quoted in literature. This algorithm can provide complete data set analysis much more quickly than manual measurements. Its use is limited by the CT resolution which means that very small branches are not visible. New data are presented on the branching angles of the airway tree.
Sauret
V
V
Department of Medical Physics and Bioengineering, Southampton General Hospital, UK.
Goatman
K A
KA
Fleming
J S
JS
Bailey
A G
AG
D000465:Algorithms; D001331:Automation; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging*; D008953:Models, Anatomic; D019047:Phantoms, Imaging; D010969:Plastics; D011877:Radionuclide Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
D010969:Plastics