Fast method for 1D non-Cartesian parallel imaging using GRAPPA
Fast method for 1D non-Cartesian parallel imaging using GRAPPA
复制标题
DOI：
10.1002/mrm.21227
复制
发表时间：
2007-06-01
影响因子：
3.3
通讯作者：
Jakob, Peter M.
中科院分区：
文献类型：
--
作者：
Heidemann, Robin M.;Griswold, Mark A.;Jakob, Peter M.
具有非笛卡尔采样方案的MRI可以提供固有的优势。已知径向采集是非常稳健的，即使在大量采样不足的情况下。这对于1D非笛卡尔MRI也是如此，其中k空间的中心被过采样或至少以奈奎斯特速率采样。更宽松的折叠伪影行为有两个主要原因：首先，由于中心的过采样，避免了源自k空间中心的高能量折叠伪影。其次，由于k空间的非等距采样，相应的视场（FOV）不再被良好地定义。因此，折叠伪影在宽范围内模糊，并且看起来不太严重。更宽松的折叠伪影行为和密集采样的中心k空间使这种类型的轨迹成为自动校准并行MRI（pMRI）技术的理想补充，例如广义自动校准部分并行采集（GRAPPA）。虽然pMRI可以从非笛卡尔轨迹中受益，但这种组合尚未进入常规临床使用。其主要原因之一是由于非笛卡尔pMRI所需的复杂计算而需要长的重建时间。在这项工作中，它表明，一个可以显着降低计算的复杂性，通过利用一些特定的属性的k-空间为基础的pMRI。
MRI with non-Cartesian sampling schemes can offer inherent advantages. Radial acquisitions are known to be very robust, even in the case of vast undersampling. This is also true for 1D non-Cartesian MRI, in which the center of k-space is oversampled or at least sampled at the Nyquist rate. There are two main reasons for the more relaxed foldover artifact behavior: First, due to the oversampling of the center, high-energy foldover artifacts originating from the center of k-space are avoided. Second, due to the non-equidistant sampling of k-space, the corresponding field of view (FOV) is no longer well defined. As a result, foldover artifacts are blurred over a broad range and appear less severe. The more relaxed foldover artifact behavior and the densely sampled central k-space make trajectories of this type an ideal complement to autocalibrated parallel MRI (pMRI) techniques, such as generalized autocalibrating partially parallel acquisitions (GRAPPA). Although pMRI can benefit from non-Cartesian trajectories, this combination has not yet entered routine clinical use. One of the main reasons for this is the need for long reconstruction times due to the complex calculations necessary for non-Cartesian pMRI. In this work it is shown that one can significantly reduce the complexity of the calculations by exploiting a few specific properties of k-space-based pMRI.