  Purpose: Bronchoscopic intervention is a widely-used clinical technique for
pulmonary diseases, which requires an accurate and topological complete airway
map for its localization and guidance. The airway map could be extracted from
chest computed tomography (CT) scans automatically by airway segmentation
methods. Due to the complex tree-like structure of the airway, preserving its
topology completeness while maintaining the segmentation accuracy is a
challenging task.
  Methods: In this paper, a long-term slice propagation (LTSP) method is
proposed for accurate airway segmentation from pathological CT scans. We also
design a two-stage end-to-end segmentation framework utilizing the LTSP method
in the decoding process. Stage 1 is used to generate a coarse feature map by an
encoder-decoder architecture. Stage 2 is to adopt the proposed LTSP method for
exploiting the continuity information and enhancing the weak airway features in
the coarse feature map. The final segmentation result is predicted from the
refined feature map.
  Results: Extensive experiments were conducted to evaluate the performance of
the proposed method on 70 clinical CT scans. The results demonstrate the
considerable improvements of the proposed method compared to some
state-of-the-art methods as most breakages are eliminated and more tiny bronchi
are detected. The ablation studies further confirm the effectiveness of the
constituents of the proposed method.
  Conclusion: Slice continuity information is beneficial to accurate airway
segmentation. Furthermore, by propagating the long-term slice feature, the
airway topology connectivity is preserved with overall segmentation accuracy
maintained.
