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中文摘要：
在低剂量计算机断层扫描CT（computed tomography）重建算法中,传统的最大似然期望最大MLEM（Maximum Likelihood Expectation Maximization）算法随着迭代次数的增加会出现棋盘效应而不能有效地抑制噪声。针对上述问题提出一种基于小波收缩和四阶各向异性扩散相结合的MLEM低剂量CT重建算法。该算法结合小波收缩和各向异性扩散的优点,在每次迭代中,对MLEM重建算法处理后的图像进行离散平稳小波分解,在小波域的高频部分进行小波收缩,低频部分使用降噪效果优质的四阶各向异性扩散进行消噪,最后残留的脉冲噪声点通过中值滤波器进行处理,从而进一步优化图像。仿真实验结果表明,该算法可以有效地去除低剂量CT图像的噪声,且在保持图像边缘和细节信息方面有很好的表现,从而获得高抗噪性能的图像。
英文摘要：
In low-dose CT（ computed tomography） reconstruction algorithm,traditional maximum likelihood expectation maximisation（ MLEM） algorithm will appear chessboard effect along with the increase of the number of iterations,thus cannot effectively suppress noises.For this problem,this paper proposes a low dose CT reconstruction algorithm,which is based on the combination of wavelet shrinkage and fourth-order anisotropic diffusion. It combines the advantages of wavelet shrinkage and anisotropic diffusion,in each iteration,it conducts the discrete stationary wavelet decomposition on the image processed with MLEM reconstruction algorithm,in high frequency part of the wavelet domain it shrinks the wavelet,in low frequency part it uses fourth-order anisotropic diffusion,which has high quality effect in denoising,to eliminate noises,it processes the final residual pulse noise points with the median filter,so that further optimises the image. Simulation experiment results show that the proposed algorithm can effectively remove the noise in low-dose CT image,and has good performances in keeping both the image edges and detailed information,thereby gains the image with high anti-noise performance.
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