A Fast Method for Reconstruction of Total-Variation MR Images With a Periodic Boundary Condition
A Fast Method for Reconstruction of Total-Variation MR Images With a Periodic Boundary Condition
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DOI：
10.1109/lsp.2013.2245502
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发表时间：
2013-02
影响因子：
3.9
通讯作者：
Yonggui Zhu;Yuying Shi
中科院分区：
文献类型：
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作者：
Yonggui Zhu;Yuying Shi
我们使用一个小的正参数将用于无约束MR图像重建的全变差函数转换为严格的凸扰动函数。采用Bregman迭代法求解改进的全变差磁共振图像(TVMRI)重建问题。采用滞后扩散不动点算法求解Bregman迭代中的极小化问题。我们使用周期边界条件和傅立叶变换来加速TVMRI重建。用真实的磁共振图像对该方法进行了数值实验验证。实验结果表明，该方法是一种非常有效的TVMRI重建方法。
We use a small positive parameter to change the total-variation function for unconstrained MR image reconstruction to a strictly convex perturbed function. Bregman iteration is applied to solve the modified total-variation MR image (TVMRI) reconstruction problem. A lagged diffusivity fixed-point algorithm is applied to solve the minimization problem in the Bregman iteration. We use the periodic boundary condition and a Fourier transform to accelerate TVMRI reconstruction. Real MR images are used to test the approach in numerical experiments. The experimental results demonstrate that the proposed method is very efficient for TVMRI reconstruction.