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.
翻译:目标: 布朗乔斯古片干预是一种广泛使用的肺病临床技术,它需要准确和地形完整的空气路径图,以便其本地化和指导。 气道图可以通过空气路分割法自动从胸部计算断层仪(CT)扫描中提取。 由于空气路结构复杂,保持其地形完整性,同时保持分层准确性是一项艰巨的任务。 方法 : 在本文件中, 提出了一种长期切片传播(LTSP)方法, 以便从病理CT扫描中准确分解空气路段。 我们还设计了一个两阶段端至端截断层框架, 在解码过程中使用 LTSP 方法。 第一阶段用于通过编码器解码结构生成粗略的特征图。 第二阶段将采用拟议的 LTSP 方法, 利用连续性信息, 提高粗略地特征图中的空气路段特征。 最后的分解结果由精细的地谱图预测。 结果: 进行了广泛的实验,以评价拟议的70 临床CT 端端至端截断段总路段分层路段的准确性结构结构框架。 第一阶段使用一种相当的精确性的研究结果, 以Screcial- smal- decalcalation法进行较精确的精确的精确性观测。