Hou Zhishang, Zhao Jun, Sun Jianqi
Annu Int Conf IEEE Eng Med Biol Soc. 2019 Jul;2019:6251-6254. doi: 10.1109/EMBC.2019.8857845.
The potential clinical application of grating-based phase contrast computed tomography (GPCCT) requires moderate scanning time to reduce the radiation dose, which are not met by traditional GPCCT phase stepping (PS) method. Previous studies have proposed the interlaced scanning method to reduce the scanning time. However, due to the projection number demanded by the analysis reconstruction algorithm, the projection and scanning time cannot be further reduced. In this paper, we proposed an iterative algorithm based on the interlaced PS scanning for GPCCT, which was capable in reducing the motion artifacts during reconstruction as the same as the inner focus (IF) method we raised before. Furthermore, the iterative procedure is expected to introduce some machine learning method and allows a lower radiation dose while maintaining the image quality. Our proposed method mainly consists of three steps: 1) Interlaced data acquisition, 2) Phase retrieval, 3) Inner focus iterative reconstruction. Through changing the virtual rotation center and merging high resolution regions, images without severe boundary blurring can be reconstructed with fast scan speed. The experiment result indicates that our method can reconstruct GPCCT data with interlaced PS scanning.
基于光栅的相衬计算机断层扫描（GPCCT）的潜在临床应用需要适度的扫描时间以降低辐射剂量，而传统的GPCCT相移（PS）方法无法满足这一要求。先前的研究提出了交错扫描方法来减少扫描时间。然而，由于分析重建算法所需的投影数量，投影和扫描时间无法进一步减少。在本文中，我们提出了一种基于交错PS扫描的GPCCT迭代算法，该算法在重建过程中能够像我们之前提出的内聚焦（IF）方法一样减少运动伪影。此外，该迭代过程有望引入一些机器学习方法，并在保持图像质量的同时降低辐射剂量。我们提出的方法主要包括三个步骤：1）交错数据采集，2）相位检索，3）内聚焦迭代重建。通过改变虚拟旋转中心并合并高分辨率区域，可以以快速扫描速度重建没有严重边界模糊的图像。实验结果表明，我们的方法可以通过交错PS扫描重建GPCCT数据。
