Iterative image reconstruction that includes a total variation regularization for radial MRI
Iterative image reconstruction that includes a total variation regularization for radial MRI
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DOI：
10.1007/s12194-015-0320-7
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发表时间：
2015-05
影响因子：
1.6
通讯作者：
Shinya Kojima;H. Shinohara;T. Hashimoto;M. Hirata;E. Ueno
中科院分区：
文献类型：
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作者：
Shinya Kojima;H. Shinohara;T. Hashimoto;M. Hirata;E. Ueno
提出了一种基于全变分正则化的径向编码的迭代图像重建方法。代数重建方法结合全变分正则化（ART_TV）的实现与正则化参数指定的权重的TV项在优化过程中。我们使用数值模拟的Shepp-Logan幻影，以及实验成像的幻影，其中包括一个矩形波图表，评估ART_TV的性能，并将其与傅里叶变换（FT）方法。通过在体模和市售MRI系统上进行实验，研究了正则化参数不同值时空间分辨率和信噪比（SNR）之间的权衡。ART_TV在调制传递函数（MTF）的评估方面劣于FT，特别是在高频下;然而，它在SNR方面优于FT。根据信噪比测量的结果，视觉印象表明，ART_TV的图像质量优于FT的猕猴桃噪声图像重建。总之，ART_TV为放射状MRI提供了改善的低SNR数据图像质量;然而，ART_TV中的正则化参数是获得FT改善的关键因素。
This paper presents an iterative image reconstruction method for radial encodings in MRI based on a total variation (TV) regularization. The algebraic reconstruction method combined with total variation regularization (ART_TV) is implemented with a regularization parameter specifying the weight of the TV term in the optimization process. We used numerical simulations of a Shepp–Logan phantom, as well as experimental imaging of a phantom that included a rectangular-wave chart, to evaluate the performance of ART_TV, and to compare it with that of the Fourier transform (FT) method. The trade-off between spatial resolution and signal-to-noise ratio (SNR) was investigated for different values of the regularization parameter by experiments on a phantom and a commercially available MRI system. ART_TV was inferior to the FT with respect to the evaluation of the modulation transfer function (MTF), especially at high frequencies; however, it outperformed the FT with regard to the SNR. In accordance with the results of SNR measurement, visual impression suggested that the image quality of ART_TV was better than that of the FT for reconstruction of a noisy image of a kiwi fruit. In conclusion, ART_TV provides radial MRI with improved image quality for low-SNR data; however, the regularization parameter in ART_TV is a critical factor for obtaining improvement over the FT.