Zhao Yuqing, Ji Dongjiang, Li Yimin, Zhao Xinyan, Lv Wenjuan, Xin Xiaohong, Han Shuo, Hu Chunhong
School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, China.
The School of Science, Tianjin University of Technology and Education, Tianjin 300222, China.
Biomed Opt Express. 2019 Dec 20;11(1):364-387. doi: 10.1364/BOE.380084. eCollection 2020 Jan 1.
Propagation-based X-ray phase-contrast imaging (PBI) is a powerful nondestructive imaging technique that can reveal the internal detailed structures in weakly absorbing samples. Extending PBI to CT (PBCT) enables high-resolution and high-contrast 3D visualization of microvasculature, which can be used for the understanding, diagnosis and therapy of diseases involving vasculopathy, such as cardiovascular disease, stroke and tumor. However, the long scan time for PBCT impedes its wider use in biomedical and preclinical microvascular studies. To address this issue, a novel CT reconstruction algorithm for PBCT is presented that aims at shortening the scan time for microvascular samples by reducing the number of projections while maintaining the high quality of reconstructed images. The proposed algorithm combines the filtered backprojection method into the iterative reconstruction framework, and a weighted guided image filtering approach (WGIF) is utilized to optimize the intermediate reconstructed images. Notably, the homogeneity assumption on the microvasculature sample is adopted as prior knowledge, and therefore, a prior image of microvasculature structures can be acquired by a k-means clustering approach. Then, the prior image is used as the guided image in the WGIF procedure to effectively suppress streaking artifacts and preserve microvasculature structures. To evaluate the effectiveness and capability of the proposed algorithm, simulation experiments on 3D microvasculature numerical phantom and real experiments with CT reconstruction on the microvasculature sample are performed. The results demonstrate that the proposed algorithm can, under noise-free and noisy conditions, significantly reduce the artifacts and effectively preserve the microvasculature structures on the reconstructed images and thus enables it to be used for clear and accurate 3D visualization of microvasculature from few-projection data. Therefore, for 3D visualization of microvasculature, the proposed algorithm can be considered an effective approach for reducing the scan time required by PBCT.
基于传播的X射线相衬成像（PBI）是一种强大的无损成像技术，能够揭示弱吸收样品的内部详细结构。将PBI扩展到CT（PBCT）可实现微血管的高分辨率和高对比度三维可视化，可用于理解、诊断和治疗涉及血管病变的疾病，如心血管疾病、中风和肿瘤。然而，PBCT的长时间扫描阻碍了其在生物医学和临床前微血管研究中的更广泛应用。为了解决这个问题，提出了一种用于PBCT的新型CT重建算法，旨在通过减少投影数量来缩短微血管样品的扫描时间，同时保持重建图像的高质量。所提出的算法将滤波反投影方法结合到迭代重建框架中，并利用加权引导图像滤波方法（WGIF）优化中间重建图像。值得注意的是，采用微血管样品的均匀性假设作为先验知识，因此，可以通过k均值聚类方法获取微血管结构的先验图像。然后，将该先验图像用作WGIF过程中的引导图像，以有效抑制条纹伪影并保留微血管结构。为了评估所提出算法的有效性和能力，对三维微血管数值模型进行了模拟实验，并对微血管样品进行了CT重建的实际实验。结果表明，所提出的算法在无噪声和有噪声条件下，都能显著减少伪影，并有效地保留重建图像上的微血管结构，从而能够从少投影数据中清晰准确地实现微血管的三维可视化。因此，对于微血管的三维可视化，所提出的算法可被视为一种减少PBCT所需扫描时间的有效方法。
