Li Xinling, Huang Yunzhi, Han Luyi, Liu Qi, He Ling, Zhang Jin, Zhang Junpeng, Zhang Jiang
School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, P.R.China.
School of Electrical Engineering and Information, Sichuan University, Chengdu 610065,
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2017 Oct 1;34(5):721-729. doi: 10.7507/1001-5515.201611011.
To better use the phase information to compensate the influence of blood flow, the phase unwrapping problem in susceptibility weighted imaging (SWI) is studied in this paper. In order to improve the accuracy of unwrapping, this paper proposes a magnitude image-guided phase unwrapping algorithm of SWI. The basic idea is as follows: (1) reduce the influence of noise by improving the rotational invariant non-local principal component analysis method (PRI-NL-PCA); (2) extract the corresponding solid region in the phase image to avoid the influence of the background noise on the phase unwrapping method; (3) use the phase compensation method to constrain the phase image reconstructed by the K-space. Finally, the reliability of the unwrapping method is evaluated by using four kinds of statistics as quantification index: the number, mean (M), variance (Var), and positive percentage (Pos) and negative percentage (Neg) of phasic error points. By comparing the simulated data with 226 sets of true head SWI data, the results show that the proposed algorithm has high accuracy compared with the classical branch cut method and the least squares method.
为了更好地利用相位信息来补偿血流的影响，本文研究了磁共振相位对比血管造影（SWI）中的相位展开问题。为了提高展开的准确性，本文提出了一种基于幅度图像引导的SWI相位展开算法。其基本思想如下：（1）通过改进旋转不变非局部主成分分析方法（PRI-NL-PCA）来降低噪声的影响；（2）在相位图像中提取相应的实体区域，以避免背景噪声对相位展开方法的影响；（3）使用相位补偿方法来约束通过K空间重建的相位图像。最后，使用四种统计量作为量化指标来评估展开方法的可靠性：相位误差点的数量、均值（M）、方差（Var）以及正百分比（Pos）和负百分比（Neg）。通过将模拟数据与226组真实头部SWI数据进行比较，结果表明，与经典的分支切割法和最小二乘法相比，该算法具有更高的准确性。
