Gradient nonlinearity calibration and correction for a compact, asymmetric magnetic resonance imaging gradient system
Gradient nonlinearity calibration and correction for a compact, asymmetric magnetic resonance imaging gradient system
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DOI：
10.1088/1361-6560/aa524f
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发表时间：
2017-01-21
影响因子：
3.5
通讯作者：
Bernstein, M. A.
中科院分区：
文献类型：
--
作者：
Tao, S.;Trzasko, J. D.;Bernstein, M. A.
由于工程上的限制，传统磁共振成像中的空间编码梯度场不可能是完全线性的，并且总是包含高阶非线性分量。如果在图像重建过程中忽略梯度非线性，则会导致图像的几何畸变。给定GNL场的估计，这种失真可以被纠正到与场估计的精度成正比的程度。梯度系统的GNL一般采用球面调和多项式模型，模型系数由电磁仿真得到。传统的全身梯度系统设计是对称的；通常，GNL建模只需要5阶以下的奇阶项。最近，开发了一种高性能的非对称梯度系统，该系统具有更复杂的GNL，需要包括奇阶和偶阶在内的高阶项来精确建模。这项工作使用迭代校准方法和ADNI（阿尔茨海默病神经成像倡议）中使用的基准幻像来表征该系统的GNL。在26 cm直径-球体-体积梯度内的不同位置扫描幻体，估计幻体中基准点的位置。使用迭代校准程序来识别模型系数，使真实基准位置与使用这些系数校正的图像估计位置之间的均方误差最小。为了检验高阶和偶阶项的影响，使用10阶以下不同阶的球面调和多项式进行校准，包括偶阶和奇阶项，或仅奇阶项。结果表明，该梯度的模型系数可以成功地估计出来。使用10阶系数校正后的残差均方根误差降至0.36 mm，其空间精度可与常规全身梯度相媲美。偶阶项对于精确的GNL建模是必要的。此外，与基于仿真的系数相比，校正后的系数提高了图像的几何精度。
Due to engineering limitations, the spatial encoding gradient fields in conventional magnetic resonance imaging cannot be perfectly linear and always contain higher-order, nonlinear components. If ignored during image reconstruction, gradient nonlinearity (GNL) manifests as image geometric distortion. Given an estimate of the GNL field, this distortion can be corrected to a degree proportional to the accuracy of the field estimate. The GNL of a gradient system is typically characterized using a spherical harmonic polynomial model with model coefficients obtained from electromagnetic simulation. Conventional whole-body gradient systems are symmetric in design; typically, only odd-order terms up to the 5th-order are required for GNL modeling. Recently, a high-performance, asymmetric gradient system was developed, which exhibits more complex GNL that requires higher-order terms including both odd-and even-orders for accurate modeling. This work characterizes the GNL of this system using an iterative calibration method and a fiducial phantom used in ADNI (Alzheimer's Disease Neuroimaging Initiative). The phantom was scanned at different locations inside the 26 cm diameter-spherical-volume of this gradient, and the positions of fiducials in the phantom were estimated. An iterative calibration procedure was utilized to identify the model coefficients that minimize the mean-squared-error between the true fiducial positions and the positions estimated from images corrected using these coefficients. To examine the effect of higher-order and even-order terms, this calibration was performed using spherical harmonic polynomial of different orders up to the 10th-order including even- and odd-order terms, or odd-order only. The results showed that the model coefficients of this gradient can be successfully estimated. The residual root-mean-squared-error after correction using up to the 10th-order coefficients was reduced to 0.36 mm, yielding spatial accuracy comparable to conventional whole-body gradients. The even-order terms were necessary for accurate GNL modeling. In addition, the calibrated coefficients improved image geometric accuracy compared with the simulation-based coefficients.