The introduction of the full paper reviews a number of papers in the open literature on fast image reconstruction and then proposes what we believe to be a faster reconstruction method, which is explained in sections 1 and 2. Section 1 presents the characteristics of the Z-line data priority reconstruction algorithm. The core of section 2 consists of: ( 1 ) we give the definition of the smallest 3D convex package, which is shown in Fig. 3; (2) on the basis of the projection relationship of cone-beam CT and the characteristics of the smallest 3D convex package of measured object, we put forward the algorithm for determining its three basic parameters; (3) we reconstruct only the voxels inside the smallest 3D convex package, thus greatly reducing its computational redundancy; for the complicated measured objects with varying cross-section shapes, we determine the smallest 3D convex packages section by section to further reduce their computational redundancy. To verify the effectiveness of our method, section 3 presents two sets of numerical simulation examples; the simulation results, given in Figs. 5 and 6 and Table 1, and their analysis show preliminarily that our method can effectively enhance the reconstruction speed of cone-beam CT and has good adaptability for complicated object measurement.%针对传统锥束CT重建全尺寸立方体空间时存在大量冗余计算的问题,文章提出一种基于被测物体最小三维凸包的快速重建方法.首先根据Z线优先重建算法的特性,给出最小三维凸包的定义,然后根据锥束CT扫描投影关系和最小三维凸包的投影特点,提出了确定最小三维凸包3个参数的相应算法,最后通过仅重建最小三维凸包内的体素的方法,显著减少了重建计算量.对于截面形状变化较大的被测物体,可采用分段确定最小三维凸包的方式进一步减少计算冗余.2组仿真实验结果表明,文中方法可有效提高锥束CT的重建速度,并对复杂被测物体具有良好的适应性.
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