Main Topic / Applications of Generative Adversarial Networks in Medical Image Processing
Super-Resolution using GAN for Medical Image Processing
2019 Volume 37 Issue 3 Pages 143-146
Details
2019 Volume 37 Issue 3 Pages 143-146
Generative Adversarial Networks (GAN) have been applied to a variety of tasks such as denoising, image transfer and super-resolution, and have been proved to be a promising way to reconstruct high quality images. In this paper, we report super-resolution method using GAN for medical image processing. Specifically, it consists of two networks: Generator that generates High Resolution images and Discriminator that distinguish a generated HR image from a real HR image. We train these two networks iteratively to obtain the generator that reconstructs HR image. We show that blurring disappears in restored HR image by using GAN and visually high quality HR image can be obtained.
