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A projection proximal-point algorithm for MR imaging using the hybrid regularization model

机译:混合正则化模型的磁共振成像投影近点算法

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In this paper, we present a fast algorithm for MR image reconstruction based on the TV-L_1/TGV-L_1 model. By utilizing the connection between the cut operator (called projection operator) and the shrink operator, the proposed algorithm adopts a semi-implicit scheme to get a compact iteration sequence so as to reduce computational cost. By combining the proximal point scheme, we can ensure that the system of linear equations to be solved at each iteration is well-conditioned. In addition, we also give convergence analysis of the proposed method. Numerical results with comparison to the split Bregman algorithm are supplied to demonstrate the efficiency of the proposed algorithm.
机译:在本文中,我们提出了一种基于TV-L_1 / TGV-L_1模型的快速MR图像重建算法。该算法利用剪切算子(称为投影算子)与收缩算子之间的联系,采用半隐式方案获得紧凑的迭代序列,从而降低了计算量。通过结合近端点方案,我们可以确保在每次迭代中要求解的线性方程组的条件良好。此外,我们还对所提方法进行了收敛性分析。数值结果与分裂的Bregman算法进行比较,以证明该算法的有效性。

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