摘要
提高锥束CT大锥角圆轨道扫描下的重建图像质量一直是CT成像技术的重要研究方向。分析了圆轨道扫描下Radon空间的Z向数据缺失特点和FDK算法的灰度下降规律,提出了一种基于椭球包围盒的锥束CT三维加权重建算法。该算法无需重排,只需利用投影数据获取重建物体的最小包围盒,并根据其内接椭球的大小和空间位置自动生成三维加权函数,在反投影阶段加入该加权函数即可实现。该算法不会引入其他伪影,计算量增加很小,并且在中心层与FDK算法等价。仿真扫描实验表明,该算法显著提高了FDK算法的准确性,减小了锥角伪影。
Improving the quality of cone-beam CT imaging under large cone angle scan has been an important research direction of CT imaging technology. This paper analyzes the characteristics of missing data along the axial direction in Radon space under circular scanning trajectory and the intensity drop rule of FDK algorithm. A three-dimensional（ 3D） weighting reconstruction algorithm is proposed for cone-beam CT based on ellipsoidal bounding box. The proposed method does not need any operation of rebinning and only uses projection data to gain the minimum bounding box of reconstructed objects. Three-dimensional weighting function can be automatically generated according to the size and spatial position of its inscribed ellipsoid,and the weighting function is added into the3 D back-projection process to achieve the algorithm. With little increase in computation,this algorithm does not introduce other artifacts and is equivalent to FDK algorithm in the mid-plane. Simulation results show that the proposed algorithm significantly improves the accuracy of FDK algorithm,and reduces the cone angle artifacts.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2016年第11期2563-2571,共9页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(51675437
51605389)
航空科学基金(2014ZE53059)
陕西省自然科学基础研究计划(2016JM5003)
中央高校基本科研业务费(3102014KYJD022)
西北工业大学研究生创意创新种子基金(Z2016075
Z2016081)项目资助
关键词
FDK算法
数据缺失
灰度下降
椭球包围盒
FDK algorithm
missing data
intensity drop
ellipsoidal bounding box
