Reconstruction of undersampled radial PatLoc imaging using total generalized variation.
Reconstruction of undersampled radial PatLoc imaging using total generalized variation.
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DOI：
10.1002/mrm.24426
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发表时间：
2013-07
影响因子：
3.3
通讯作者：
Stollberger R
中科院分区：
文献类型：
--
作者：
Knoll F;Schultz G;Bredies K;Gallichan D;Zaitsev M;Hennig J;Stollberger R
在具有非线性空间编码场的径向成像的情况下，如果用欠采样轨迹对自旋分布进行编码，则观察到显著的星形伪影。本文提出了一种新的基于全广义变分(TGV)的迭代重建方法，减少了这种伪影。对于这种方法，需要一个采样操作符(以及它的伴随项)来将数据从PatLoc k空间映射到最终的图像空间。结果表明，这可以用由类型1和类型2非均匀FFT组合实现的类型3非均匀FFT实现。使用该算子还可以实现一种基于迭代共轭梯度(CG)意义的PatLoc重建方法，与传统的PatLoc图像重建方法相比，这导致了显著的计算时间减少。给出了数值模拟和体内PatLoc测量的结果，结果表明，基于TGV的方法在图像质量方面有显著改善。
In the case of radial imaging with nonlinear spatial encoding fields, a prominent star-shaped artifact has been observed if a spin distribution is encoded with an undersampled trajectory. This work presents a new iterative reconstruction method based on the total generalized variation (TGV), which reduces this artifact. For this approach, a sampling operator (as well as its adjoint) is needed that maps data from PatLoc k-space to the final image space. It is shown that this can be realized as a Type-3 non-uniform FFT, which is implemented by a combination of a Type-1 and Type-2 non-uniform FFT. Using this operator, it is also possible to implement an iterative conjugate gradient (CG) SENSE based method for PatLoc reconstruction, which leads to a significant reduction of computation time in comparison to conventional PatLoc image reconstruction methods. Results from numerical simulations and in-vivo PatLoc measurements with as few as 16 radial projections are presented, which demonstrate significant improvements in image quality with the TGV based approach.