CC-DA: Cross-Domain Consistency Data Augmentation for 3D Tumor Segmentation-Reference-Cited by-同舟云学术

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CC-DA: Cross-Domain Consistency Data Augmentation for 3D Tumor Segmentation

Published:2024-04-14 Issue: Volume:5 Page:1936-1940
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

He Jiezhou¹,Luo Zhiming²,Peng Wei³,Su Songzhi²,Li Shaozi²

Affiliation:

1. Institute of Artificial Intelligence, Xiamen University,Xiamen,China,361005

2. Xiamen University,Department of Artificial Intelligence,Xiamen,China,361005

3. Stanford University,Department of Psychiatry and Behavioral Sciences,CA,United States,94305

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province

Wuyi University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446129.pdf?arnumber=10446129

Reference20 articles.

1. Towards Simultaneous Segmentation Of Liver Tumors And Intrahepatic Vessels Via Cross-Attention Mechanism

2. Adaptive Pseudo Labeling for Source-Free Domain Adaptation in Medical Image Segmentation

3. Deep learning based brain tumor segmentation: a survey

4. Automatic Data Augmentation Via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation

5. TumorGAN: A Multi-Modal Data Augmentation Framework for Brain Tumor Segmentation

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