| Autor: |
Xiao CHANG, Xin CAI, Guang YANG, Sheng-dong NIE |
| Jazyk: |
čínština |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Chinese Journal of Magnetic Resonance, Vol 39, Iss 03, Pp 366-380 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1000-4556 |
| DOI: |
10.11938/cjmr20212962 |
| Popis: |
In recent years, the generative adversarial network (GAN) has attracted widespread attention with its unique adversarial training mechanism. Its applications have gradually extended to the field of medical imaging, and much excellent research has emerged. This paper reviews the research progress of the popular application for GAN in medical image translation. It starts with an introduction to the basic concepts of GAN and its typical variants, emphasizing on several GANs related to medical image translation. Then, the recent progress is summarized and analyzed from the perspectives of different target tasks and training modes. Finally, the remaining challenges of GAN in medical image translation and the directions of future development are discussed. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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