TY - JOUR
T1 - A faster image reconstruction method for cone-beam CT using smallest 3D convex package of measured object
AU - Li, Mingjun
AU - Zhang, Dinghua
AU - Huang, Kuidong
AU - Zhang, Shunli
AU - Zha, Fanglong
PY - 2011/2
Y1 - 2011/2
N2 - 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.
AB - 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.
KW - Algorithms
KW - Cone-beam CT
KW - Image reconstruction
KW - Smallest three-dimensional convex package
KW - Z-line data priority reconstruction algorithm
UR - http://www.scopus.com/inward/record.url?scp=79953815553&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:79953815553
SN - 1000-2758
VL - 29
SP - 68
EP - 73
JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
IS - 1
ER -