Comparison of Ring Artifacts Removal by Using Neural Network in Different Domains

Abstract

Ring artifacts in CT imaging has been blamed for many years. If not removed, these rings will severely deteriorate the image quality and affect doctor’s diagnosis results. Existed ring artifacts removal methods are generally based on filtering and averaging. In this paper, we propose a new ring artifacts removal method by using neural networks. We apply deep learning techniques respectively in image domain, projection domain and polar coordinate system. Besides, in the past, ring artifacts removal is performed either in image domain or projection domain independently. In this paper, by incorporating reconstruction process into neural network, we unite the image domain and projection domain processing for ring artifacts removal in the framework of deep learning. Traditional methods are implemented for comparison. Quantitative analysis is performed and it shows that the comprehensive neural network model including both image domain and projection domain information achieves the best results.