Airway Tree Modeling (ATM'22) Related Work

Official repository for MICCAI 2022 Challenge: Multi-site, Multi-Domain Airway Tree Modeling (ATM’22).

By Minghui Zhang, Yangqian Wu, Hanxiao Zhang, Yulei Qin, Hao Zheng, Xiaoxuan Zheng, Fangfang Xie, Jiayuan Sun, Guang-Zhong Yang, Yun Gu

The organization team of the ATM'22, Institute of Medical Robotics, Shanghai Jiao Tong University & Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital

Participation Instruction
Related Pulmonary Airway Segmentation Work
Dataset Rule

Participation Instruction

Our challenge is open call (challenge opens for new submissions after MICCAI 2022 deadline).

Registration

The registration page and detailed information could refer to the Registration Page.

Baseline and Docker Tutorial

We provide a baseline model and a detailed docker tutorial, please refer to: Baseline and Docker Example for detailed instructions.

Evaluation

The evaluation code is provided in Evaluation.

Related Pulmonary Airway Segmentation Work

We collected the papers related to pulmonary airway segmentation and bronchoscopy navigation as belows:

Date	Author	Title	Conf/Jour	Code
2022	Wehao Yu	TNN: Tree Neural Network for Airway Anatomical Labeling	IEEE TMI	Official
2022	Yun Gu	Vision-Kinematics-Interaction for Robotic-Assisted Bronchoscopy Navigation	IEEE TMI	——
2022	Minghui Zhang	CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway TreeModeling of COVID-19 CTs	MICCAI	Official
2022	Haifan Gong	BronchusNet: Region and Structure Prior Embedded Representation Learning for Bronchus Segmentation and Classification	Arxiv	——
2021	Wehao Yu	BREAK: Bronchi Reconstruction by gEodesic transformation And sKeleton embedding	ISBI	——
2021	Yangqian Wu	LTSP: long-term slice propagation for accurate airway segmentation	IJCARS	——
2021	Minghui Zhang	Fda: Feature decomposition and aggregation for robust airway segmentation	DART@MICCAI	——
2021	Hao Zheng	Refined Local-imbalance-based Weight for Airway Segmentation in CT	MICCAI	Official
2021	Hao Zheng	Alleviating class-wise gradient imbalance for pulmonary airway segmentation	IEEE TMI	Official
2021	A. Garcia-Uceda Juarez	Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks	Scientific Reports	Official
2020	Hanxiao Zhang	Pathological airway segmentation with cascaded neural networks for bronchoscopic navigation	IEEE ICRA	——
2020	Yulei Qin	Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CT	IEEE TMI	Official
2020	Raghavendra Selvan	Graph refinement based airway extraction using mean-field networks and graph neural networks	MIA	Official
2019	Jihye Yun	Improvement of fully automated airway segmentation on volumetric computed tomographic images using a 2.5 dimensional convolutional neural net	MIA	——
2019	Chenglong Wang	Tubular structure segmentation using spatial fully connected network with radial distance loss for 3D medical images	MICCAI	——
2019	A. Garcia-Uceda Juarez	A joint 3D UNet-graph neural network-based method for airway segmentation from chest CTs	MLMI@MICCAI	——
2019	Yulei Qin	AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networks	MICCAI	——
2017	Qier Meng	Tracking and segmentation of the airways in chest CT using a fully convolutional network	MICCAI	——
2017	Jean-Paul Charbonnier	Improving airway segmentation in computed tomography using leak detection with convolutional networks	MIA	——
2017	Dakai Jin	3D convolutional neural networks with graph refinement for airway segmentation using incomplete data labels	MLMI@MICCAI	——
2015	Ziyue Xu	A hybrid method for airway segmentation and automated measurement of bronchial wall thickness on CT	MIA	——
2012	Pechin Lo	Extraction of airways from CT (EXACT'09)	IEEE TMI	——

Dataset Rule

If you find this repo's papers and codes are helpful to your research, and if you use our dataset provided by ATM'22 for your scientific research, please cite the following works:

@incollection{zhang2021fda,
  title={Fda: Feature decomposition and aggregation for robust airway segmentation},
  author={Zhang, Minghui and Yu, Xin and Zhang, Hanxiao and Zheng, Hao and Yu, Weihao and Pan, Hong and Cai, Xiangran and Gu, Yun},
  booktitle={Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health},
  pages={25--34},
  year={2021},
  publisher={Springer}
}

@article{zheng2021alleviating,
  title={Alleviating class-wise gradient imbalance for pulmonary airway segmentation},
  author={Zheng, Hao and Qin, Yulei and Gu, Yun and Xie, Fangfang and Yang, Jie and Sun, Jiayuan and Yang, Guang-Zhong},
  journal={IEEE Transactions on Medical Imaging},
  volume={40},
  number={9},
  pages={2452--2462},
  year={2021},
  publisher={IEEE}
}

@inproceedings{yu2022break,
  title={BREAK: Bronchi Reconstruction by gEodesic transformation And sKeleton embedding},
  author={Yu, Weihao and Zheng, Hao and Zhang, Minghui and Zhang, Hanxiao and Sun, Jiayuan and Yang, Jie},
  booktitle={2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)},
  pages={1--5},
  year={2022},
  organization={IEEE}
}

@inproceedings{qin2019airwaynet,
  title={Airwaynet: a voxel-connectivity aware approach for accurate airway segmentation using convolutional neural networks},
  author={Qin, Yulei and Chen, Mingjian and Zheng, Hao and Gu, Yun and Shen, Mali and Yang, Jie and Huang, Xiaolin and Zhu, Yue-Min and Yang, Guang-Zhong},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={212--220},
  year={2019},
  organization={Springer}
}

ALVINU/ATM-22-Related-Work