Linearized proximal alternating direction method of multipliers for parallel magnetic resonance imaging

Linearized proximal alternating direction method of multipliers for parallel magnetic resonance imaging
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DOI:
10.1109/jas.2016.7510226
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发表时间:
2017-10
期刊:
IEEE/CAA Journal of Automatica Sinica
影响因子:
--
通讯作者:
Benxin Zhang;Zhibin Zhu
Benxin Zhang;Zhibin Zhu
中科院分区:
其他
文献类型:
--
作者:
Benxin Zhang;Zhibin Zhu

文献摘要

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在这项研究中,我们提出了一种线性化的变步长近邻交替方向法来解决全变差图像重建问题。我们的方法使用了线性化技术和近似函数,因此可以很容易地导出子问题的闭合形式解。在子问题中,我们采用了一种类似于Barzilai-Borwein步长的可变步长来加速算法。并行磁共振成像的数值结果验证了该算法的有效性。
In this study, we propose a linearized proximal alternating direction method with variable stepsize for solving total variation image reconstruction problems. Our method uses a linearized technique and the proximal function such that the closed form solutions of the subproblem can be easily derived. In the subproblem, we apply a variable stepsize, that is like Barzilai-Borwein stepsize, to accelerate the algorithm. Numerical results with parallel magnetic resonance imaging demonstrate the efficiency of the proposed algorithm.