摘要
滤波反投影算法已被广泛应用到CT图像重建领域,但由于算法需要大量的投影数据,会延长扫描时间和累积高剂量的辐射。为了降低辐射的剂量,文中提出一种基于压缩传感和联合代数重建方法 (SART)的迭代算法,将图像的梯度稀疏性与SART图像重建相结合,减小梯度图像的l1范数直至算法迭代结束。实验结果表明,文中算法能利用少量的投影数据准确地重建出图像,减少了由于投影数据不充分而造成的条状伪影。
The filtered back projection （FBP） algorithm has been commonly exploited in CT image reconstruction, but this algorithm requires a large amount of projection data, prolonging scanning time, and cumulating with a high dose of radiation is possible. To obtain lower radiation dose, this paper presents an iterative algorithm based on the compressed sensing and simultaneous algebraic reconstruction technique （SART） , combines the gradient sparsity of image with SART image reconstruction to minimize the 11 -norm of the gradient image. The experimental results show that the proposed algorithm can use a small mount of projection data to reconstruct image accurately and reduce the impact of artifacts introduced into the reconstructed image due to the insufficient projection information.
出处
《信息技术》
2013年第7期136-139,142,共5页
Information Technology
关键词
图像重建
压缩传感
SART算法
低辐射剂量
image reconstruction
compressed sensing
SART algorithm
lower radiation dose
