Propagation-based x-ray phase-contrast computed tomography (PB-PCCT) images often suffer from severe ring artifacts. Ring artifacts are mainly caused by the nonuniform response of detector elements, and they can degrade image quality and affect the subsequent image processing and quantitative analyses. To remove ring artifacts in PB-PCCT images, a novel method combined sparse-domain regularized stripe decomposition (SDRSD) method with guided image filtering (GIF) was proposed. In this method, polar coordinate transformation was utilized to convert the ring artifacts to stripe artifacts. And then considering the directional and sparse properties of the stripe artifacts and the continuity characteristics of the sample, the SDRSD method was designed to remove stripe artifacts. However, for the SDRSD method, the presence of noise may destroy the edges of the stripe artifacts and lead to incomplete decomposition. Hence, a simple and efficient smoothing technique, namely GIF, was employed to overcome this issue. The simulations and real experiments demonstrated that the proposed method could effectively remove ring artifacts as well as preserve the structures and edges of the samples. In conclusion, the proposed method can serve as an effective tool to remove ring artifacts in PB-PCCT images, and it has high potential for promoting the biomedical and preclinical applications of PB-PCCT.

基于传播的 X 射线相衬计算机断层扫描 (PB-PCCT) 图像经常遭受严重的环形伪影。环形伪影主要是由于探测器元件响应不均匀引起的，它们会降低图像质量并影响后续的图像处理和定量分析。为了去除PB-PCCT图像中的环形伪影，提出了一种将稀疏域正则化条带分解（SDRSD）方法与引导图像滤波（GIF）相结合的新方法。在该方法中，利用极坐标变换将环形伪影转换为条纹伪影。然后考虑条纹伪影的方向性和稀疏性以及样本的连续性特点，设计了SDRSD方法去除条纹伪影。然而，对于 SDRSD 方法，噪声的存在可能会破坏条纹伪影的边缘并导致不完全分解。因此，一种简单而有效的平滑技术，即 GIF，被用来解决这个问题。仿真和真实实验表明，所提出的方法可以有效去除环形伪影，并保留样品的结构和边缘。总之，所提出的方法可以作为去除PB-PCCT图像中环形伪影的有效工具，具有促进PB-PCCT的生物医学和临床前应用的潜力。仿真和真实实验表明，所提出的方法可以有效去除环形伪影，并保留样品的结构和边缘。总之，所提出的方法可以作为去除PB-PCCT图像中环形伪影的有效工具，具有促进PB-PCCT的生物医学和临床前应用的潜力。仿真和真实实验表明，所提出的方法可以有效去除环形伪影，并保留样品的结构和边缘。总之，所提出的方法可以作为去除PB-PCCT图像中环形伪影的有效工具，具有促进PB-PCCT的生物医学和临床前应用的潜力。