目的 提出基于投影数据全广义变分最小化的低剂量CT重建方法.方法 首先,通过非线性Anscombe变换将满足Poisson分布的投影数据转化为近似Gaussian分布,然后基于全广义变分正则化模型对变换后的Gaussian型数据进行噪声去除.最后,对去噪的结果进行Anscombe逆变换后实现传统的滤波反投影(FBP)CT重建.结果 数值体膜实验结果表明本文提出的方法可以大大地改进重建图像的质量.FBP方法重建的Clock和Shepp-Logan体膜图像的信噪比分别为17.752 dB和19.379 dB,本文方法重建的图像的信噪比提高到24.0352 dB和23.4181 dB.FBP方法重建方法重建的Clock和Shepp-Logan体膜图像的均方误差分别为0.86%和0.58%,本文方法重建的图像的均方误差降低到到0.2%和0.23%.结论 本文方法可以在投影数据不满足分段常数假设的前提下去除噪声和条形伪影,从而提高低剂量CT图像重建质量.%Objective To obtain high-quality low-dose CT images using total generalized variation regularization based on the projection data for low-dose CT reconstruction.Methods The projection data of the CT images were transformed from Poisson distribution to Gaussian distribution using the linear Anscombe transform. The transformed data were then restored by an efficient total generalized variation minimization algorithm. Reconstruction was finally achieved by inverse Anscombe transform and filtered back projection(FBP)method.Results The image quality of low-dose CT was greatly improved by the proposed algorithm in both Clock and Shepp-Logan phantoms. The signal-to-noise ratios (SNRs) of the Clock and Shepp-Logan images reconstructed by FBP algorithm were 17.752 dB and 19.379 dB,which were increased by the proposed algorithm to 24.0352 and 23.4181 dB,respectively.The NMSE of the Clock and Shepp-Logan images reconstructed by FBP algorithm was 0.86% and 0.58%,which was reduced by the proposed algorithm to 0.2% and 0.23%,respectively.Conclusion The proposed method can effectively suppress noise and strip artifacts in low-dose CT images when piecewise constant assumption is not possible.
展开▼
