GAN-Based Medical Images Synthesis

Abstract

Medical images have always occupied a very important position in modern medical diagnosis. They are standard tools for doctors to carry out clinical diagnosis. However, nowadays, most clinical diagnosis relies on the doctors' professional knowledge and personal experience, which can be easily affected by many factors. In order to reduce the diagnosis errors caused by human subjective differences and improve the accuracy and reliability of the diagnosis results, a practical and reliable method is to use artificial intelligence technology to assist computer-aided diagnosis (CAD). With the help of powerful computer storage capabilities and advanced artificial intelligence algorithms, CAD can make up for the shortcomings of traditional manual diagnosis and realize efficient, intelligent diagnosis. This paper reviews GAN-based medical image synthesis methods, introduces the basic architecture and important improvements of GAN, lists some representative application examples, and finally makes a summary and discussion.