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摘要: 如何实现快速磁共振成像(Magnetic resonance imaging, MRI)是MRI医学图像技术发展和应用的关键, 现有的快速MRI成像技术在成像速度及成像质量方面仍存在很大的提升空间.本文基于Contourlet变换, 对磁共振图像进行稀疏表示, 并结合传统PF-CS-SENSE框架, 提出一种基于Contourlet变换的组合MRI重构方法, 即PF-FICOTA-SENSE.考虑到组合MRI采样模式、低频数据的对称性以及Contourlet能更好地拟合曲线轮廓等因素, 进一步提出一种快速组合MRI方法, 该方法通过将低频部分重建由FICOTA重建替换为直接填零的傅里叶重建, 来实现快速重建.对比实验表明, 无论在MRI重构速度还是重构质量方面, 本文算法均能取得更好的性能.
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关键词:
- 压缩感知 /
- 半傅里叶成像 /
- 并行成像 /
- PF-FICOTA-SENSE
Abstract: How to realize rapid magnetic resonance imaging (MRI) is the key to the development and applications of MRI. The existing rapid MRI imaging technology still has much room for improvement in imaging rate and imaging quality. Based on Contourlet which is used to transform the sparse representation of magnetic resonance images, this paper proposes a combined MRI reconstruction method named PF-FICOTA-SENSE that is combined with the traditional PF-CS-SENSE framework. Considering the combination of MRI sampling mode, the symmetry of the low frequency data and Contourlet's ability to express curve contours, a fast combined MRI method for direct zero-filled Fourier reconstruction of low-frequency parts is proposed based on the proposed PF-FICOTA-SENSE. The contrast experiments show that the proposed method can achieve better performance in terms of MRI reconstruction speed and reconstruction quality.-
Key words:
- Compressed sensing /
- partial Fourier imaging /
- parallel imaging /
- PF-FICOTA-SENSE
1) 本文责任编委 桑农 -
表 1 SFLCT不同配置下的冗余度数据
Table 1 SFLCT redundancy data in different configurations
$d$ $\omega_{p, 0}$ $\omega_{s, 0}$ $\omega_{p, 1}$ $\omega_{s, 1}$ 冗余度 1 $\frac{\pi}{3}$ $\frac{2\pi}{3}$ $\frac{\pi}{6}$ $\frac{\pi}{3}$ 2.33 1.5 $\frac{5\pi}{14}$ $\frac{9\pi}{14}$ $\frac{19\pi}{72}$ $\frac{35\pi}{72}$ 1.60 2 $\frac{4\pi}{21}$ $\frac{10\pi}{21}$ $\frac{4\pi}{21}$ $\frac{10\pi}{21}$ 1.33 表 2 三种方法的重建性能比较(ROI)
Table 2 Reconstruction performance comparison (ROI) on three different methods
PF-FICOTA-SENSE PF-DTFCSA-SENSE PF-CS-SENSE 稀疏表示 SFLCT Complex DT Daubechies-4 重建时间(s) $\sim$150 $\sim$120 $\sim$150 $R_{Total} = 6$
$R_{CS} \approx 1.8$CC 0.9825 0.9816 0.9779 PSNR 75.1207 74.7429 74.1084 NMSE 0.0033 0.0036 0.0041 $R_{Total} = 10$
$R_{CS} \approx 3.2$CC 0.9717 0.9724 0.9557 PSNR 73.0758 73.0504 71.1287 NMSE 0.0052 0.0053 0.0082 表 3 三种方法的快速组合MRI重建性能比较(ROI)
Table 3 Reconstruction performance comparison (ROI) on fast combined MRI of three different methods
PF-FICOTA-SENSE PF-DTFCSA-SENSE PF-CS-SENSE 组合框架 原型 快速 原型 快速 原型 快速 重建时间(s) $\sim$150 $\sim$75 $\sim$120 $\sim$60 $\sim$150 $\sim$75 $R_{Total} = 6$
$R_{CS} \approx 1.8$CC 0.9825 0.9824 0.9816 0.9815 0.9779 0.9779 PSNR 75.1207 75.1079 74.7429 74.7293 74.1084 74.1021 NMSE 0.0033 0.0033 0.0036 0.0036 0.0041 0.0041 $R_{Total} = 10$
$R_{CS} \approx 3.2$CC 0.9717 0.9717 0.9724 0.9723 0.9557 0.9557 PSNR 73.0758 73.0670 73.0504 73.0384 71.1287 71.1277 NMSE 0.0052 0.0052 0.0053 0.0053 0.0082 0.0082 表 4 三种方法的快速组合MRI峰值信噪比(PSNR)损失率(ROI)
Table 4 Peak signal-to-noise ratio (PSNR) loss rate (ROI) on fast combined MRI of three different methods
PSNR损失率($\times{10}^{-4}$) PF-FICOTA-SENSE PF-DTFCSA-SENSE PF-CS-SENSE $R_{Total} = 6$
$R_{CS} \approx 1.8$1.7039 1.8199 0.8501 $R_{Total} = 10$
$R_{CS} \approx 3.2$1.2041 1.6427 0.1406 -
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