mlsanityData to 7 Oct 2026

Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation

arXiv 2303.05745 ↗First posted 10 Mar 2023eess.IV cs.CVcited by 9

Not on the map. Why?

Abstract (arXiv)

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and clinical drive for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 51 of its 120 references that are in the map. First posted on arXiv 10 Mar 2023.

Builds on

51 of 120 references.

References · 51

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  4. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 6,979
  5. 2016Densely Connected Convolutional Networkscited by 6,691
  6. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,284
  7. 20163D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotationcited by 1,471
  8. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,420
  9. 2016Instance Normalization: The Missing Ingredient for Fast Stylizationcited by 1,187
  10. 2017A Closer Look at Spatiotemporal Convolutions for Action Recognitioncited by 1,139
  11. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,018
  12. 2019Large-Scale Long-Tailed Recognition in an Open Worldcited by 704
38 more
  1. 2016Language Modeling with Gated Convolutional Networkscited by 688
  2. 2021The Medical Segmentation Decathloncited by 620
  3. 2017Skin Lesion Analysis Toward Melanoma Detection: A Challenge at the 2017 International Symposium on Biomedical Imaging (ISBI), Hosted by the International Skin Imaging Collaboration (ISIC)cited by 549
  4. 2017A systematic study of the class imbalance problem in convolutional neural networkscited by 510
  5. 2021Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysiscited by 418
  6. 2020clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentationcited by 286
  7. 2019ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed datacited by 260
  8. 2020AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?cited by 222
  9. 2019Topology-Preserving Deep Image Segmentationcited by 198
  10. 2018Boundary loss for highly unbalanced segmentationcited by 187
  11. 2019A Topological Loss Function for Deep-Learning based Image Segmentation using Persistent Homologycited by 134
  12. 2018BACH: Grand Challenge on Breast Cancer Histology Imagescited by 131
  13. 2019Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challengecited by 100
  14. 2021Contextual Transformer Networks for Visual Recognitioncited by 90
  15. 2018Combo Loss: Handling Input and Output Imbalance in Multi-Organ Segmentationcited by 76
  16. 2021Topology-Aware Segmentation Using Discrete Morse Theorycited by 75
  17. 2018AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomycited by 54
  18. 2019Deep Distance Transform for Tubular Structure Segmentation in CT Scanscited by 52
  19. 2018Deep Learning using Rectified Linear Units (ReLU)cited by 43
  20. 2019Shape-Aware Organ Segmentation by Predicting Signed Distance Mapscited by 41
  21. 2020Alleviating Class-wise Gradient Imbalance for Pulmonary Airway Segmentationcited by 34
  22. 2019AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networkscited by 32
  23. 2020Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CTcited by 28
  24. 2019A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTscited by 27
  25. 2018Automatic Airway Segmentation in chest CT using Convolutional Neural Networkscited by 18
  26. 2021Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networkscited by 18
  27. 2022Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentationcited by 18
  28. 2022BREAK: Bronchi Reconstruction by gEodesic transformation And sKeleton embeddingcited by 16
  29. 2022Human Treelike Tubular Structure Segmentation: A Comprehensive Review and Future Perspectivescited by 14
  30. 2021FDA: Feature Decomposition and Aggregation for Robust Airway Segmentationcited by 12
  31. 2021The RETA Benchmark for Retinal Vascular Tree Analysiscited by 12
  32. 2022Local Intensity Order Transformation for Robust Curvilinear Object Segmentationcited by 12
  33. 2019`Project & Excite' Modules for Segmentation of Volumetric Medical Scanscited by 7
  34. 2022Structure and position-aware graph neural network for airway labelingcited by 6
  35. 2022LTSP: Long-Term Slice Propagation for Accurate Airway Segmentationcited by 6
  36. 2018Divergence Prior and Vessel-tree Reconstructioncited by 4
  37. 2018Extraction of Airways using Graph Neural Networkscited by 3
  38. 2021Confluent Vessel Trees with Accurate Bifurcationscited by 3

50 most cited of 51 All 51 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 1; 2025: 2; 2026: 1.

9 papers.

  1. 2025nnInteractive: Redefining 3D Promptable Segmentationcited by 39
  2. 2023Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelinescited by 17
  3. 2025MIMO: A medical vision language model with visual referring multimodal input and pixel grounding multimodal outputcited by 14
  4. 2023HybridMIM: A Hybrid Masked Image Modeling Framework for 3D Medical Image Segmentationcited by 12
  5. 2023Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learningcited by 7
  6. 2023Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Datasetcited by 6
  7. 2024A Geometric Algorithm for Blood Vessel Reconstruction from Skeletal Representationcited by 1
  8. 2023Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performancecited by 0
  9. 2026Learning Topology-Aware Implicit Field for Unified Pulmonary Tree Modeling with Incomplete Topological Supervisioncited by 0