Self-calibrated GRAPPA method for 2D and 3D radial data
Self-calibrated GRAPPA method for 2D and 3D radial data
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DOI：
10.1002/mrm.21223
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发表时间：
2007-05-01
影响因子：
3.3
通讯作者：
Block, Walter F.
中科院分区：
文献类型：
--
作者：
Arunachalam, Arjun;Samsonov, Alexey;Block, Walter F.
提出了一种快速并行MRI（pMRI）重建方法，用于2D和3D径向轨迹。径向广义自动校准部分并行采集（GRAPPA）方法的局限性是需要在实际扫描之前采集训练数据。这可以通过在合成每个线圈重建的缺失数据时使用自校准来消除。每个线圈的训练数据通过将常规重建的复合图像与每个线圈的空间灵敏度分布相乘来估计，所述复合图像包含来自欠采样的混叠伪影。从满足奈奎斯特采样标准的k空间数据获得个体接收器空间灵敏度分布的估计。然后，在所采集的k空间样本点处以及在我们期望合成k空间数据的未采集位置处计算训练数据的频域表示。将采集的k空间样本拟合到未采集的点创建重建权重，用于合成未采集的径向线。二维径向轨迹的方法在体内的可行性与二维腹部成像的例子说明。初步结果后，应用该方法对三维径向稳态自由进动（SSFP）数据集也证明。
A fast parallel MRI (pMRI) reconstruction method is presented for 2D and 3D radial trajectories. A limitation of the radial generalized autocalibrating partially parallel acquisitions (GRAPPA) method is the need to acquire training data prior to the actual scan. This can be eliminated by the use of self-calibration when synthesizing the missing data for each coil reconstruction. The training data for each coil are estimated by multiplying the conventionally reconstructed composite image, which contains the aliasing artifacts from undersampling, with each coil's spatial sensitivity profile. An estimate of the individual receiver spatial sensitivity profiles is obtained from the k-space data that fulfill the Nyquist sampling criterion. The frequency domain representation of the training data is then calculated at the acquired k-space sample points and at the unacquired locations at which we desire to synthesize k-space data. Fitting the acquired k-space samples to the unacquired points creates reconstruction weights that are used to synthesize unacquired radial lines. The in vivo feasibility of the method for 2D radial trajectories is illustrated with an example of 2D abdominal imaging. Preliminary results obtained after applying the method on a 3D radial steady-state free precession (SSFP) data set are also demonstrated.