Applications of generative adversarial networks in medical image processing.

Author: Dan PAN ^{1
,

2} ; Longfei JIA ³ ; An ZENG ^{4
,

5} ; Xiaowei SONG ⁶
Author Information

1. Modern Education Technology Center, Guangdong Construction Polytechnic, Guangzhou 510440, P.R.China
2. Guangzhou Benzhen Networks Technology Co. Ltd., Guangzhou 510000, P.R.China.
3. Faculty of Computer, Guangdong University of Technology, Guangzhou 510006, P.R.China.
4. Faculty of Computer, Guangdong University of Technology, Guangzhou 510006, P.R.China
5. Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou 510006, P.R.China.
6. ImageTech Lab, Simon Fraser University, Vancouver V6B 5K3, Canada.
Publication Type:Journal Article
Keywords: deep learning; generative adversarial networks; medical images
From: Journal of Biomedical Engineering 2018;35(6):970-976
CountryChina
Language:Chinese
Abstract: In recent years, researchers have introduced various methods in many domains into medical image processing so that its effectiveness and efficiency can be improved to some extent. The applications of generative adversarial networks (GAN) in medical image processing are evolving very fast. In this paper, the state of the art in this area has been reviewed. Firstly, the basic concepts of the GAN were introduced. And then, from the perspectives of the medical image denoising, detection, segmentation, synthesis, reconstruction and classification, the applications of the GAN were summarized. Finally, prospects for further research in this area were presented.