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Application of generative adversarial networks in cardiac magnetic resonance
LIU Weixiao  FANG Jin  WANG Ying  MO Xiaokai  ZHANG Shuixing 

Cite this article as: LIU W X, FANG J, WANG Y, et al. Application of generative adversarial networks in cardiac magnetic resonance[J]. Chin J Magn Reson Imaging, 2023, 14(6): 139-144. DOI:10.12015/issn.1674-8034.2023.06.025.


[Abstract] Cardiac magnetic resonance (CMR) is an important examination method for evaluating cardiovascular structure and function. Deep learning has been widely used in CMR image processing. Generative adversarial network (GAN), as a new type of network in deep learning, uses the adversarial game between the generator responsible for image generation and the discriminator responsible for judging the authenticity of images to create image processing models with powerful generation and generalization capabilities. We summarized the main applications of GAN in CMR image segmentation and synthesis, image reconstruction, super-resolution reconstruction, and virtual native enhancement in this paper. Combined with the current clinical application requirements of CMR, we analyzed the challenges and future prospects faced by GAN models in order to improve their practical application value as soon as possible.
[Keywords] cardiac magnetic resonance；image processing；generative adversarial network；deep learning；artificial intelligence；magnetic resonance imaging

LIU Weixiao   FANG Jin   WANG Ying   MO Xiaokai   ZHANG Shuixing*  

Department of Radiology, the First Affiliated Hospital of Jinan University, Guangzhou 510000, China

Corresponding author: Zhang SX, E-mail: shui7515@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81871323); Medical Science and Technology Research Fund of Guangdong Province (No. A2022267); Fundamental Research Funds for the Central Universities (No. 21621050).
Received  2023-01-11
Accepted  2023-04-23
DOI: 10.12015/issn.1674-8034.2023.06.025
Cite this article as: LIU W X, FANG J, WANG Y, et al. Application of generative adversarial networks in cardiac magnetic resonance[J]. Chin J Magn Reson Imaging, 2023, 14(6): 139-144. DOI:10.12015/issn.1674-8034.2023.06.025.

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