为了提高能谱X-CT重建图像的质量,提出了利用能量加权重建图像xbins^W及可分离抛物面替代法进行基于先验图像和约束压缩感知的能谱X-CT图像重建.利用压缩感知理论、先验图像和优化算法来提高CT重建图像的质量.为了评价所提方法的性能,从重建的各能量段图像精度和噪声特性2个方面比较了3种优化算法及3种先验图像.仿真实验结果表明,对于不同的优化算法,能量加权重建图像xbins^W作为先验图像总体性能最佳;对于不同的先验图像,可分离抛物面替代法算法性能最佳.与滤波反投影算法相比,在基于先验图像约束和压缩感知的能谱X-CT图像重建算法中,采用SPS算法进行优化,采用能量加权重建图像作为先验图像,重建得到的各能量段的图像噪声分别降低了80.46%,82.51%,88.08%,每个能量段图像的均方根误差分别下降了15.02%,18.15%和34.11%,相关系数分别提高了9.98%,11.38%和15.94%.
To improve spectral X-ray CT reconstructed image quality, the energy-weighted reconstructed image xbins^W and the separable paraboloidal surrogates(SPS) algorithm are proposed for the prior image constrained compressed sensing(PICCS)-based spectral X-ray CT image reconstruction. The PICCS-based image reconstruction takes advantage of the compressed sensing theory, a prior image and an optimization algorithm to improve the image quality of CT reconstructions.To evaluate the performance of the proposed method, three optimization algorithms and three prior images are employed and compared in terms of reconstruction accuracy and noise characteristics of the reconstructed images in each energy bin.The experimental simulation results show that the image xbins^W is the best as the prior image in general with respect to the three optimization algorithms; and the SPS algorithm offers the best performance for the simulated phantom with respect to the three prior images. Compared with filtered back-projection(FBP), the PICCS via the SPS algorithm and xbins^W as the prior image can offer the noise reduction in the reconstructed images up to 80. 46%, 82. 51%, 88. 08% in each energy bin,respectively. M eanwhile, the root-mean-squared error in each energy bin is decreased by 15. 02%, 18. 15%, 34. 11% and the correlation coefficient is increased by 9. 98%, 11. 38%,15. 94%, respectively.