Bao Yuan, Wang Yan, Li Panyun, Wu Zhao, Shao Qigang, Gao Kun, Wang Zhili, Ju Zaiqiang, Zhang Kai, Yuan Qingxi, Huang Wanxia, Zhu Peiping, Wu Ziyu
National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, Anhui 230029, People's Republic of China.
Institute of High Energy Physics, Chinese Academy of Science, Beijing 100049, People's Republic of China.
J Synchrotron Radiat. 2015 May;22(3):786-95. doi: 10.1107/S1600577515003616. Epub 2015 Apr 8.
A description of the rocking curve in diffraction enhanced imaging (DEI) is presented in terms of the angular signal response function and a simple multi-information retrieval algorithm based on the cosine function fitting. A comprehensive analysis of noise properties of DEI is also given considering the noise transfer characteristic of the X-ray source. The validation has been performed with synchrotron radiation experimental data and Monte Carlo simulations based on the Geant4 toolkit combined with the refractive process of X-rays, which show good agreement with each other. Moreover, results indicate that the signal-to-noise ratios of the refraction and scattering images are about one order of magnitude better than that of the absorption image at the edges of low-Z samples. The noise penalty is drastically reduced with the increasing photon flux and visibility. Finally, this work demonstrates that the analytical method can build an interesting connection between DEI and GDPCI (grating-based differential phase contrast imaging) and is widely suitable for a variety of measurement noise in the angular signal response imaging prototype. The analysis significantly contributes to the understanding of noise characteristics of DEI images and may allow improvements to the signal-to-noise ratio in biomedical and material science imaging.
本文根据角信号响应函数和基于余弦函数拟合的简单多信息检索算法,对衍射增强成像(DEI)中的摇摆曲线进行了描述。考虑到X射线源的噪声传递特性,还对DEI的噪声特性进行了全面分析。利用同步辐射实验数据以及基于Geant4工具包并结合X射线折射过程的蒙特卡罗模拟进行了验证,结果显示二者吻合良好。此外,结果表明,在低Z值样品边缘处,折射图像和散射图像的信噪比比分吸收图像约高一个数量级。随着光子通量和可见度的增加,噪声惩罚大幅降低。最后,这项工作表明,该分析方法能够在DEI和基于光栅的微分相衬成像(GDPCI)之间建立有趣的联系,并且广泛适用于角信号响应成像原型中的各种测量噪声。该分析对理解DEI图像的噪声特性有显著贡献,可能有助于提高生物医学和材料科学成像中的信噪比。