A CT Local Reconstruction Algorithm Based on Prior Image and Compressed Sensing
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摘要: 为了提高CT图像局部重建的质量,在压缩感知理论的基础上提出基于先验图像-压缩感知的CT局部重建算法.首先对获得的局部感兴趣区域内的投影数据进行滤波反投影重建,并将重建的CT图像作为迭代的初始图像;然后以图像的总变差最小化为原则对局部感兴趣区域进行凸集投影总变差最小化重建.以Shepp-Logan模型和某型固体火箭发动机为例进行实验的结果表明,该算法能够获得更好的CT图像局部重建质量,且具有更强的抑噪性能.
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关键词:
- 局部重建 /
- 先验图像 /
- 压缩感知 /
- 滤波反投影 /
- 凸集投影总变差最小化
Abstract: In order to improve the local reconstruction quality of CT images, a CT local reconstruction algorithm based on prior images and compressed sensing（CS） was proposed on the basis of CS theory. First, the filtered backprojection（FBP） algorithm was used to reconstruct the projection data in local region of interest（ROI）, and the reconstructed CT image was adopted as the prior image of iteration. Then the total variation minimization（TVM） of CT image was chosen as the criterion for the projection onto convex sets-TVM reconstruction of local ROI. Shepp-Logan model and one solid rocket motor were chosen to carry out relative experiment. Results show that the proposed algorithm has better local reconstruction quality of CT images and anti-noise performance. -
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