School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, 300070, People's Republic of China.
School of Science, Tianjin University of Technology and Education, Tianjin 300222, People's Republic of China.
Phys Med Biol. 2021 May 14;66(10). doi: 10.1088/1361-6560/abf9de.
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成像（PB-PCCT）图像常常受到严重的环状伪影的影响。环状伪影主要是由探测器元件的非均匀响应引起的，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 图像中的环状伪影，提出了一种将稀疏域正则条纹分解（SDRSD）方法与导向图像滤波（GIF）相结合的新方法。在该方法中，利用极坐标变换将环状伪影转换为条纹伪影。然后，考虑到条纹伪影的方向和稀疏特性以及样本的连续性特征，设计了 SDRSD 方法来去除条纹伪影。然而，对于 SDRSD 方法，噪声的存在可能会破坏条纹伪影的边缘，导致不完全分解。因此，采用了一种简单而有效的平滑技术，即 GIF，来克服这个问题。模拟和实际实验表明，所提出的方法可以有效地去除环状伪影，同时保留样本的结构和边缘。总之，该方法可以作为一种有效的工具来去除 PB-PCCT 图像中的环状伪影，具有促进 PB-PCCT 在生物医学和临床前应用的潜力。
