Record link: 
http://hdl.handle.net/20.500.12708/208877
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Title: 
Cross-domain attention-guided generative data augmentation for medical image analysis with limited data
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Citation: 
Xu, Z., Tang, J., Qi, C., Yao, D., Liu, C., Zhan, Y., & Lukasiewicz, T. (2024). Cross-domain attention-guided generative data augmentation for medical image analysis with limited data. Computers in Biology and Medicine, 168, Article 107744. https://doi.org/10.1016/J.COMPBIOMED.2023.107744
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Publisher DOI: 
10.1016/J.COMPBIOMED.2023.107744
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Publication Type: 
Article - Original Research Article
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Language: 
English
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Authors: 
Xu, Zhenghua 
Tang, Jiaqi 
Qi, Chang 
Yao, Dan 
Liu, Caihua 
Zhan, Yuefu 
Lukasiewicz, Thomas 
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Organisational Unit: 
E192-07 - Forschungsbereich Artificial Intelligence Techniques 
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Journal: 
Computers in Biology and Medicine 
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ISSN: 
0010-4825
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Date (published): 
Jan-2024
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Publisher: 
PERGAMON-ELSEVIER SCIENCE LTD
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Peer reviewed: 
Yes
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Keywords: 
medical image segmentation; data augmentation; generative adversarial networks (GANs); cross-domain tumor image generation; semi-supervised spatial attention
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 80%
1010 - Mathematik: 20%
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