2D-GRAPPA-operator for faster 3D parallel MRI
2D-GRAPPA-operator for faster 3D parallel MRI
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DOI：
10.1002/mrm.21071
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发表时间：
2006-12-01
影响因子：
3.3
通讯作者：
Jakob, Peter M.
中科院分区：
文献类型：
--
作者：
Blaimer, Martin;Breuer, Felix A.;Jakob, Peter M.
当结合三维（3D）成像使用并行MRI（pMRI）方法时，沿着两个相位编码方向对k空间沿着进行二次采样是有益的，因为然后可以利用沿着沿着两个空间维度的线圈灵敏度变化。这导致改进的重建质量，并且因此与沿沿着一维的子采样相比允许更大的扫描时间减少。在这项工作中，我们提出了一种新的方法的基础上，广义自动校准部分并行采集（GRAPPA）技术，允许傅立叶域重建的数据集，沿沿着两个维度进行二次采样。该方法通过将2D重建过程分成两个单独的1D重建来工作。这种方法相比，传统的GRAPPA方法，直接再生丢失的数据点的2D二次采样的k-空间，通过执行一个线性组合的采集数据点的扩展。在本文中，我们描述的理论背景和目前的计算机模拟和在体内实验。
When using parallel MRI (pMRI) methods in combination with three-dimensional (3D) imaging, it is beneficial to subsample the k-space along both phase-encoding directions because one can then take advantage of coil sensitivity variations along two spatial dimensions. This results in an improved reconstruction quality and therefore allows greater scan time reductions as compared to subsampling along one dimension. In this work we present a new approach based on the generalized autocalibrating partially parallel acquisitions (GRAPPA) technique that allows Fourier-domain reconstructions of data sets that are subsampled along two dimensions. The method works by splitting the 2D reconstruction process into two separate 1D reconstructions. This approach is compared with an extension of the conventional GRAPPA method that directly regenerates missing data points of a 2D subsampled k-space by performing a linear combination of acquired data points. In this paper we describe the theoretical background and present computer simulations and in vivo experiments.