Ring artifacts suppression for X-ray CT images by fusion of dual-domain images based on improved UNet

人工智能 轮廓波 工件(错误) 计算机视觉 图像质量 计算机科学 峰值信噪比 图像融合 模式识别(心理学) 均方误差 领域(数学分析) 图像(数学) 戒指(化学) 噪音(视频) 相似性(几何) 数学 统计 小波变换 数学分析 化学 有机化学 小波
作者
Dalong Tan,Yapeng Wu,Penghui He,Chao Hai,Liang Sun,Min Yang
出处
期刊:Research Square - Research Square [Research Square (United States)]
标识
DOI:10.21203/rs.3.rs-2997609/v1
摘要

Abstract The ring artifact is one of the typical artifacts in X-ray Computed Tomography (CT) images. The existence of ring artifacts will reduce the image quality, change the structure and details of the image, and affect the interpretation of image information. How to effectively suppress ring artifacts has always been an important research direction in the industrial and medical CT fields. In this research, three experiments of CT scanning were designed by using the microfocus cone-beam CT system, we take the real CT image sequences as datasets, and design customized loss functions according to the characteristics of the ring artifacts based on the structure of UNet, in addition, a model for suppressing ring artifacts is designed both in the slice domain and sinogram domain. Then, the outputs of the dual domain are fused using the Nonsubsampled Contourlet Transform algorithm. The network model is trained and tested using the real datasets, then Peak Signal-to-Noise Ratio (PSNR), Structural Similarity (SSIM), and mean squared error (MSE) are used as the evaluation indicators of image quality. Finally, the proposed method is compared with the typical algorithms of artifact suppression, and the experimental results show that the method proposed in this research can protect the structure information in CT images while suppressing the ring artifacts to the greatest extent, and the PSNR, SSIM, and MSE of the processed images can respectively reach 39.3 dB, 98.9 and 5.2×e− 4.

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