Generative Adversarial Networks in Medical Image Processing.

Journal: Current pharmaceutical design
Published Date:

Abstract

BACKGROUND: The emergence of generative adversarial networks (GANs) has provided new technology and framework for the application of medical images. Specifically, a GAN requires little to no labeled data to obtain high-quality data that can be generated through competition between the generator and discriminator networks. Therefore, GANs are rapidly proving to be a state-of-the-art foundation, achieving enhanced performances in various medical applications.

Authors

  • Meiqin Gong
    West China Second University Hospital, Sichuan University, Chengdu 610041, China.
  • Siyu Chen
    School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.
  • Qingyuan Chen
    School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.
  • Yuanqi Zeng
    School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.
  • Yongqing Zhang
    School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China.