Fig. 2
From: A Custom Annotated Dataset for Segmentation of Pulmonary Veins, Arteries, and Airways
Visual Analysis of Annotation Style Differences on External Datasets. This figure compares segmentation results from our AirRC-trained model against the reference annotations from the ATM'22 and HiPas datasets to illustrate differences in labeling philosophy. The color scheme highlights these differences: blue indicates regions segmented only by our model (reflecting our annotation style); red indicates regions labeled only in the external dataset’s ground truth; and yellow represents the consensus on the core anatomical structures. Panels (a,b) show an Airway Lumen from the ATM'22 dataset in coronal and 3D views. Panels (c,d) and (e,f) show the Pulmonary Arteries and Veins, respectively, from a HiPas case. In all instances, the predominance of yellow demonstrates a strong foundational agreement on the main structures. The key observation is the consistent pattern of blue voxels at the distal ends of the vascular and airway trees. This visually confirms that our model, trained on the detailed AirRC annotations, consistently identifies more peripheral, finer-caliber branches. While these are anatomically plausible, they are penalized as False Positives when evaluated against a reference standard with a different scope of annotation, which explains the performance gap observed in our external validation.
