LTSP: Long-Term Slice Propagation for Accurate Airway Segmentation
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 10 of its 22 references that are in the map. First posted on arXiv 13 Feb 2022.
Builds on
10 of 22 references.
References · 10
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
- 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,471
- 2017Spatial As Deep: Spatial CNN for Traffic Scene Understandingcited by 187
- 2019AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networkscited by 32
- 2019A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTscited by 27
- 2018Automatic Airway Segmentation in chest CT using Convolutional Neural Networkscited by 18
- 2021Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networkscited by 18
- 2021FDA: Feature Decomposition and Aggregation for Robust Airway Segmentationcited by 12
Built on by
Citing papers per year: 2022: 3; 2023: 2; 2024: 1.
6 papers.
- 2022NaviAirway: a Bronchiole-sensitive Deep Learning-based Airway Segmentation Pipelinecited by 17
- 2023Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentationcited by 9
- 2022Extraction of Pulmonary Airway in CT Scans Using Deep Fully Convolutional Networkscited by 2
- 2022Differentiable Topology-Preserved Distance Transform for Pulmonary Airway Segmentationcited by 2
- 2024Progressive Curriculum Learning with Scale-Enhanced U-Net for Continuous Airway Segmentationcited by 2
- 2023Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performancecited by 0
- 2024Progressive Curriculum Learning with Scale-Enhanced U-Net for Continuous Airway Segmentation24 Oct 2024
- 2023Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance29 Jul 2023
- 2023Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation10 Mar 2023
- 2022Differentiable Topology-Preserved Distance Transform for Pulmonary Airway Segmentation17 Sep 2022
- 2022Extraction of Pulmonary Airway in CT Scans Using Deep Fully Convolutional Networks12 Aug 2022
- 2022NaviAirway: a Bronchiole-sensitive Deep Learning-based Airway Segmentation Pipeline8 Mar 2022