Beijing Key Laboratory of Medical Physics and Engineering, Peking University, Beijing, PR China.
Magn Reson Med. 2009 Oct;62(4):1085-90. doi: 10.1002/mrm.22074.
In MRI, phase maps can provide useful information about parameters such as field inhomogeneity, velocity of blood flow, and the chemical shift between water and fat. As phase is defined in the (-pi,pi] range, however, phase wraps often occur, which complicates image analysis and interpretation. This work presents a two-dimensional phase unwrapping algorithm that uses quality-guided region growing and local linear estimation. The quality map employs the variance of the second-order partial derivatives of the phase as the quality criterion. Phase information from unwrapped neighboring pixels is used to predict the correct phase of the current pixel using a linear regression method. The algorithm was tested on both simulated and real data, and is shown to successfully unwrap phase images that are corrupted by noise and have rapidly changing phase.
在 MRI 中,相位图可以提供有关参数的有用信息,例如磁场不均匀性、血流速度以及水和脂肪之间的化学位移。然而,由于相位定义在(-pi,pi]范围内,因此经常会发生相位缠绕,这使得图像分析和解释变得复杂。本工作提出了一种二维相位解缠算法,该算法使用质量引导的区域生长和局部线性估计。质量图采用相位的二阶偏导数的方差作为质量标准。使用线性回归方法,根据相邻已解缠像素的相位信息来预测当前像素的正确相位。该算法在模拟和真实数据上进行了测试,结果表明该算法可以成功解缠受到噪声和相位快速变化影响的相位图像。