Generative Adversarial Networks in Medical Image augmentation: A review

With the development of deep learning, the number of training samples for medical image-based diagnosis and treatment models is increasing. Generative Adversarial Networks (GANs) have attracted attention in medical image processing due to their excellent image generation capabilities and have been w...

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Veröffentlicht in:	Computers in biology and medicine Jg. 144; S. 105382
Hauptverfasser:	Chen, Yizhou, Yang, Xu-Hua, Wei, Zihan, Heidari, Ali Asghar, Zheng, Nenggan, Li, Zhicheng, Chen, Huiling, Hu, Haigen, Zhou, Qianwei, Guan, Qiu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Ltd 01.05.2022 Elsevier Limited
Schlagworte:	Augmentation Data augmentation Datasets Deep learning Diagnosis Generative adversarial networks Image processing Image Processing, Computer-Assisted - methods Image synthesis Internal Medicine Machine learning Medical diagnosis Medical image Medical imaging Medical research Methods Neural Networks, Computer Optimization Organs Other Researchers Reviews Sample size Statistical methods Training Augmentation Deep learning Medical image Generative adversarial networks Image synthesis
ISSN:	0010-4825, 1879-0534, 1879-0534
Online-Zugang:	Volltext
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