Array compression for MRI with large coil arrays
Array compression for MRI with large coil arrays
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DOI：
10.1002/mrm.21237
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发表时间：
2007-06-01
影响因子：
3.3
通讯作者：
Kozerke, Sebastian
中科院分区：
文献类型：
--
作者：
Buehrer, Martin;Pruessmann, Klaas P.;Kozerke, Sebastian
具有大量独立线圈元件的阵列正变得越来越可用，因为它们提供了更高的信噪比（SNRs）和改进的并行成像性能。然而，处理来自大量独立接收通道的数据会增加重构中的内存和计算负荷。这项工作通过引入线圈阵列压缩来解决这个问题。该方法允许通过在图像重建之前将时域中的全部或部分集组合在一起来减少来自独立通道的数据集的数量。结果表明，根据感兴趣区域（ROI）的大小，阵列压缩可以非常有效。基于在心脏中使用32单元相控阵线圈获得的二维体内数据，表明在环绕心脏的ROI中，通道数量可以被压缩到4个，而信噪比损失仅为0.3%。在使用相同的压缩系数时，两次平行成像的信噪比损失仅为2%。
Arrays with large numbers of independent coil elements are becoming increasingly available as they provide increased signal-to-noise ratios (SNRs) and improved parallel imaging performance. Processing of data from a large set of independent receive channels is, however, associated with an increased memory and computational load in reconstruction. This work addresses this problem by introducing coil array compression. The method allows one to reduce the number of datasets from independent channels by combining all or partial sets in the time domain prior to image reconstruction. It is demonstrated that array compression can be very effective depending on the size of the region of interest (ROI). Based on 2D in vivo data obtained with a 32-element phased-array coil in the heart, it is shown that the number of channels can be compressed to as few as four with only 0.3% SNR loss in an ROI encompassing the heart. With twofold parallel imaging, only a 2% loss in SNR occurred using the same compression factor.