PROCEEDINGS ARTICLE | February 24, 2010
Proc. SPIE. 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
KEYWORDS: Detection and tracking algorithms, Data modeling, Image segmentation, Image processing, Lung, Nomenclature, Computed tomography, Algorithm development, Statistical modeling, Chronic obstructive pulmonary disease
The bronchial tree is of direct clinical importance in the context of respective diseases, such as chronic obstructive
pulmonary disease (COPD). It furthermore constitutes a reference structure for object localization in the lungs and it
finally provides access to lung tissue in, e.g., bronchoscope based procedures for diagnosis and therapy. This paper
presents a comprehensive anatomical model for the bronchial tree, including statistics of position, relative and absolute
orientation, length, and radius of 34 bronchial segments, going beyond previously published results. The model has been
built from 16 manually annotated CT scans, covering several branching variants. The model is represented as a
centerline/tree structure but can also be converted in a surface representation. Possible model applications are either to
anatomically label extracted bronchial trees or to improve the tree extraction itself by identifying missing segments or
sub-trees, e.g., if located beyond a bronchial stenosis. Bronchial tree labeling is achieved using a naïve Bayesian
classifier based on the segment properties contained in the model in combination with tree matching. The tree matching
step makes use of branching variations covered by the model. An evaluation of the model has been performed in a leaveone-
out manner. In total, 87% of the branches resulting from preceding airway tree segmentation could be correctly
labeled. The individualized model enables the detection of missing branches, allowing a targeted search, e.g., a local rerun
of the tree-segmentation segmentation.
