mlsanityData to 7 Oct 2026

Human Treelike Tubular Structure Segmentation: A Comprehensive Review and Future Perspectives

arXiv 2207.11203 ↗First posted 12 Jul 2022eess.IV cs.CV cs.LGcited by 14

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Abstract (arXiv)

Various structures in human physiology follow a treelike morphology, which often expresses complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal blood vessels, and hepatic blood vessels. Large collections of 2D and 3D images have been made available by medical imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), Optical coherence tomography (OCT) and ultrasound in which the spatial arrangement can be observed. Segmentation of these structures in medical imaging is of great importance since the analysis of the structure provides insights into disease diagnosis, treatment planning, and prognosis. Manually labelling extensive data by radiologists is often time-consuming and error-prone. As a result, automated or semi-automated computational models have become a popular research field of medical imaging in the past two decades, and many have been developed to date. In this survey, we aim to provide a comprehensive review of currently publicly available datasets, segmentation algorithms, and evaluation metrics. In addition, current challenges and future research directions are discussed.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 26 of its 155 references that are in the map. First posted on arXiv 12 Jul 2022.

Builds on

26 of 155 references.

References · 26

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
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  6. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
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  11. 2016Least Squares Generative Adversarial Networkscited by 1,000
  12. 2020clDice -- A Novel Topology-Preserving Loss Function for Tubular Structure Segmentationcited by 286
14 more
  1. 2019Learning Lightweight Lane Detection CNNs by Self Attention Distillationcited by 162
  2. 2021Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyondcited by 75
  3. 2018DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumescited by 62
  4. 2018AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomycited by 54
  5. 2020Alleviating Class-wise Gradient Imbalance for Pulmonary Airway Segmentationcited by 34
  6. 2019AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networkscited by 32
  7. 2020Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CTcited by 28
  8. 2019A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTscited by 27
  9. 2022Data Harmonisation for Information Fusion in Digital Healthcare: A State-of-the-Art Systematic Review, Meta-Analysis and Future Research Directionscited by 19
  10. 2018Automatic Airway Segmentation in chest CT using Convolutional Neural Networkscited by 18
  11. 2021Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networkscited by 18
  12. 2019`Project & Excite' Modules for Segmentation of Volumetric Medical Scanscited by 7
  13. 2018Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networkscited by 4
  14. 2019A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentationcited by 4

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Citing papers per year: 2022: 2; 2023: 3; 2024: 4; 2025: 5.

14 papers.

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  1. 2022Fuzzy Attention Neural Network to Tackle Discontinuity in Airway Segmentationcited by 18
  2. 2023Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challengecited by 12
  3. 2023Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentationcited by 9
  4. 2022Large-Kernel Attention for 3D Medical Image Segmentationcited by 7
  5. 2024Intensity Confusion Matters: An Intensity-Distance Guided Loss for Bronchus Segmentationcited by 6
  6. 20233D Vessel Segmentation with Limited Guidance of 2D Structure-agnostic Vessel Annotationscited by 5
  7. 2025HarmonySeg: Tubular Structure Segmentation with Deep-Shallow Feature Fusion and Growth-Suppression Balanced Losscited by 3
  8. 2024Make it more specific: A novel uncertainty based airway segmentation application on 3D U-Net and its variantscited by 1
  9. 2024Probing Perfection: The Relentless Art of Meddling for Pulmonary Airway Segmentation from HRCT via a Human-AI Collaboration Based Active Learning Methodcited by 1
  10. 2025RefTr: Recurrent Refinement of Confluent Trajectories for 3D Vascular Tree Centerlinescited by 1
  11. 2024Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structurescited by 0
  12. 2025Predicting Patient Survival with Airway Biomarkers using nn-Unet/Radiomicscited by 0
2 more
  1. 2025Airway Segmentation Network for Enhanced Tubular Feature Extractioncited by 0
  2. 2025Rethinking the Detail-Preserved Completion of Complex Tubular Structures based on Point Cloud: a Dataset and a Benchmarkcited by 0