Dual Consistency Learning for Semi-Supervised Airway Segmentation-Reference-Cited by-同舟云学术

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Dual Consistency Learning for Semi-Supervised Airway Segmentation

Published:2024-06-12 Issue: Volume:172 Page:961-967
ISSN:
Container-title:2024 2nd International Conference on Mechatronics, IoT and Industrial Informatics (ICMIII)
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Author:

Li Mingshuang¹,Yuan Yunyi²,Wang Qiong³,Qian Yinling³,Zhu Lei⁴

Affiliation:

1. Southern University of Science and Technology,Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China

2. Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen,China

3. Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology,Shenzhen,China

4. The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10659854/10659821/10660124.pdf?arnumber=10660124

Reference24 articles.

1. AirwayNet: A Voxel-Connectivity Aware Approach for Accurate Airway Segmentation Using Convolutional Neural Networks

2. A Joint 3D UNet-Graph Neural Network-Based Method for Airway Segmentation from Chest CTs

3. Frequency Domain Channel-wise Attack to CNN Classifiers in Motor Imagery Brain-Computer Interfaces

4. Towards A Relation Extractor Nested U-Architecture for Accurate Pulmonary Airway Segmentation in CT images

5. LTSP: long-term slice propagation for accurate airway segmentation

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