Brain image conversion method based on generative adversarial network
Nuan Qiu, Dapeng Cheng, Chengnuo Li, Yajie Li · 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) · 2021
In recent years, brain image conversion technology has become popular in the field of medical imaging, and plays a very important auxiliary role in clinical diagnosis and disease detection of brain diseases, such as brain image reconstruction, brain image noise reduction and brain image segmentation. The brain image conversion technology aims to learn the mapping relationship between two different modal brain images, and can convert one modal brain image into another modal brain image. However, there are complex relationships between different modal data, and there is no unified theoretical framework to realize the conversion between different modal data. Therefore, we propose a brain image conversion method based on generative adversarial network to realize the conversion between different modal brain images, and prove the superiority of this method through experiments.