RT-GROG: Parallelized Self-Calibrating GROG for Real-Time MRI
RT-GROG: Parallelized Self-Calibrating GROG for Real-Time MRI
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DOI：
10.1002/mrm.22351
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发表时间：
2010-07-01
影响因子：
3.3
通讯作者：
Seiberlich, Nicole
中科院分区：
文献类型：
--
作者：
Saybasili, Haris;Derbyshire, J. Andrew;Seiberlich, Nicole
提出了一种用于径向捕获的自校准广义自动校准部分并行采集(GRAPPA)算子网格的实时实现方法。自校准GRAPPA算子网格化是一种基于并行成像的、无参数的网格化算法，其中使用线圈灵敏度分布来计算网格权重。自标定GRAPPA算子网格化的权集计算和图像重建步骤被解耦为两个不同的过程，并用C++实现并行化。这种去耦合允许权重在背景中自适应地更新，而图像重建线程使用最新的网格权重来网格和重建图像。二维网格权重G(X)(M)G(Y)(N)的所有可能组合被评估为m，n={-0.5，-0.4，...，0，0.1，...，0.5}，并存储在查找表中。因此，从重建过程中省去了网格化过程中每个样本的二维权重计算，代之以简单的查找表访问。在实践中，重建速度比传统的(并行化)自校准GRAPPA算子网格快34倍。在一个大小为128x的32线圈数据集上，重建性能为14.5帧/秒(Fps)，而数据采集为6.6fps。医学院：第306-312页，2010年。(C)2010年Wiley-Liss公司
A real-time implementation of self-calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self-calibrating GRAPPA operator gridding is a parallel-imaging-based, parameter-free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self-calibrating GRAPPA operator gridding's weight-set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C++ and parallelized. This decoupling allows the weights to be updated adaptively in the background while image reconstruction threads use the most recent gridding weights to grid and reconstruct images. All possible combinations of two-dimensional gridding weights G(x)(m)G(y)(n) are evaluated for m,n = {-0.5, -0.4, ..., 0, 0.1, ..., 0.5} and stored in a look-up table. Consequently, the per-sample two-dimensional weights calculation during gridding is eliminated from the reconstruction process and replaced by a simple look-up table access. In practice, up to 34x faster reconstruction than conventional (parallelized) self-calibrating GRAPPA operator gridding is achieved. On a 32-coil dataset of size 128 x 64, reconstruction performance is 14.5 frames per second (fps), while the data acquisition is 6.6 fps. Magn Reson Med 64:306-312, 2010. (C) 2010 Wiley-Liss, Inc.