Table 1.
Patients baseline characteristics.
Fig 1.
Work-flow chart for fully automatic lung lobe segmentation.
A: The initial step is the segmentation of the airway tree. B: Second, central airways and lobar bronchi are labeled by an anatomical knowledge-based algorithm. C: Then, a convex hull around the labeled lobar bronchi is generated. D: In the next step vasculature is iteratively subsequently segmented as far into the lung periphery as possible and added to the corresponding lobe by distance measures. E: Lastly, fissures are detected by eigenvalue/eigenvector operations (sagittal view right and left lung). F: Final results of automatic lobe segmentation using bronchi, vessel and fissure information as volume rendering images in posterior view. Lobes are indicated as follows: yellow = right superior lobe, green = middle lobe, orange = right inferior lobe, light blue = left superior lobe, red = lingual, pink = left inferior lobe.
Fig 2.
Representative example of the manual correction process of the automatically segmented lung lobes.
Coronal as well as sagittal views of the right lung are shown for the original CT data and the results after automatic lobe segmentation (“automatic”) in this CF patient. The course of the fissures was already satisfactorily detected by the software. Manual correction lead to a smoother delineation but did not substantially change the position of the margins of the lobes. Lobes are indicated as follows: yellow = right superior lobe, green = middle lobe, blue = right inferior lobe, light blue = left superior lobe, maroon = lingual, purple magenta = left inferior lobe.
Table 2.
Summary for Dice index, mean differences in segmented volume and air trapping on B30f scans.
Table 3.
Temporal development of lung volume and air trapping over 24 months.