Published May 28, 2022
| Version v1
Dataset
Open
Dataset Validation Images for the MICCAI-2022-Challenge: Airway Tree Modeling (ATM'22)
Authors/Creators
- 1. Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
Description
Dataset for the MICCAI-2022-Challenge: Airway Tree Modeling (ATM'22)
This is the Validation Image part.
If you use this dataset in your research, you must cite the papers in the References below !!!
Files
Files
(8.8 GB)
| Name | Size | |
|---|---|---|
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md5:b9df4b732e2db0f0035001b3a505b750
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8.8 GB | Download |
Additional details
References
- Zhang M, Wu Y, Zhang H, et al. Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation[J]. arXiv preprint arXiv:2303.05745, 2023.
- Zhang M, Zhang H, Yang G Z, et al. CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs[C]//Medical Image Computing and Computer Assisted Intervention–MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part I. Cham: Springer Nature Switzerland, 2022: 506-516.
- Zheng H, Qin Y, Gu Y, et al. Alleviating class-wise gradient imbalance for pulmonary airway segmentation[J]. IEEE Transactions on Medical Imaging, 2021, 40(9): 2452-2462.
- Yu W, Zheng H, Zhang M, et al. BREAK: Bronchi Reconstruction by gEodesic transformation And sKeleton embedding[C]//2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE, 2022: 1-5.
- Qin Y, Chen M, Zheng H, et al. Airwaynet: a voxel-connectivity aware approach for accurate airway segmentation using convolutional neural networks[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019: 212-220.