Improving k-t SENSE by adaptive regularization
Improving k-t SENSE by adaptive regularization
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DOI：
10.1002/mrm.21203
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发表时间：
2007-05-01
影响因子：
3.3
通讯作者：
Liang, Zhi-Pei
中科院分区：
文献类型：
--
作者：
Xu, Dan;King, Kevin F.;Liang, Zhi-Pei
最近提出的称为 k-t 灵敏度编码 (SENSE) 的方法已成为提高多种动态成像应用的成像速度的有效手段。然而，k-t SENSE 使用时间平均数据作为图像重建的正则化项。这不仅可能会损害时间分辨率，还可能使一些时间频率分量无法恢复。为了解决这个问题，我们提出了一种新方法，称为基于时空域的去混叠，采用灵敏度编码和自适应正则化（SPEAR）。具体来说，SPEAR 通过生成自适应正则化图像，对 k-t SENSE 进行了改进。它还使用可变密度 (VD)、顺序交错 k-t 空间采样模式和参考帧进行数据采集。基于实验数据的模拟对SPEAR、k-t SENSE和其他几种相关方法进行了比较，结果表明SPEAR可以提供更高的时间分辨率，同时显着减少图像伪影。还进行了非门控 3D 心脏成像实验来测试 SPEAR 的有效性，并以 5.5 帧/秒的时间分辨率和 2.4 x 1.2 x 8 mm(3) 的空间分辨率和八个切片生成人类心脏的实时 3D 短轴图像。
The recently proposed method known as k-t sensitivity encoding (SENSE) has emerged as an effective means of improving imaging speed for several dynamic imaging applications. However, k-t SENSE uses temporally averaged data as a regularization term for image reconstruction. This may not only compromise temporal resolution, it may also make some of the temporal frequency components irrecoverable. To address that issue, we present a new method called spatiotemporal domain based unaliasing employing sensitivity encoding and adaptive regularization (SPEAR). Specifically, SPEAR provides an improvement over k-t SENSE by generating adaptive regularization images. It also uses a variable-density (VD), sequentially interleaved k-t space sampling pattern with reference frames for data acquisition. Simulations based on experimental data were performed to compare SPEAR, k-t SENSE, and several other related methods, and the results showed that SPEAR can provide higher temporal resolution with significantly reduced image artifacts. Ungated 3D cardiac imaging experiments were also carried out to test the effectiveness of SPEAR, and real time 3D short-axis images of the human heart were produced at 5.5 frames/s temporal resolution and 2.4 x 1.2 x 8 mm(3) spatial resolution with eight slices.