A Review on Generative Adversarial Networks used for Image Reconstruction in Medical imaging
Robin Kumar, Rahul Malik · 2021
In computer vision, Because of its capacity to generate data, generative adversarial networks have gotten much interest. Generative Adversarial Network (GANs) opens different ways to overcome difficulties in medical image investigations like de-noising of the captured image, reconstruction of captured medical image, segmentation of the captured medical image, synthesis of the captured image, detection and classification of processed medical image. GANs great potentials in image restoration or reconstruction for different anatomy open a new research area. However, image reconstruction for specific anatomy is still facing the challenge. This article consists of a recent literature review on the applications of GAN for the reconstruction of medical images. Different reconstruction methods in the field of medical imaging were explored in this paper thoroughly. We have studied the foremost relevant publications.