scholarly journals A half-covered helical cone-beam reconstruction algorithm based on the Radon inversion transformation

2015 ◽  
Vol 64 (5) ◽  
pp. 058704
Author(s):  
Han Yu ◽  
Li Lei ◽  
Yan Bin ◽  
Xi Xiao-Qi ◽  
Hu Guo-En
Keyword(s):  
Reconstruction Algorithm ◽  
Cone Beam ◽  
Inversion Transformation ◽  
Cone Beam Reconstruction

Near Real-Time X-Ray Cone-Beam Microtomography

1999 ◽  
Vol 5 (S2) ◽  
pp. 940-941
Author(s):  
Shih Ang ◽  
Wang Ge ◽  
Cheng Ping-Chin
Keyword(s):  
Reconstruction Algorithm ◽  
Cone Beam ◽  
Reconstruction Process ◽  
X Ray ◽  
Beam Geometry ◽  
Cone Beam Reconstruction ◽  
Cylindrical Coordinate ◽  
Contrast Mechanism ◽  
Penetration Ability ◽  
Set Up

Due to the penetration ability and absorption contrast mechanism, cone-beam X-ray microtomography is a powerful tool in studying 3D microstructures in opaque specimens. In contrast to the conventional parallel and fan-beam geometry, the cone-beam tomography set up is highly desirable for faster data acquisition, build-in magnification, better radiation utilization and easier hardware implementation. However, the major draw back of the cone-beam reconstruction is its computational complexity. In an effort to maximize the reconstruction speed, we have developed a generalized Feldkamp cone-beam reconstruction algorithm to optimize the reconstruction process. We report here the use of curved voxels in a cylindrical coordinate system and mapping tables to further improve the reconstruction efficiency.The generalized Feldkamp cone-beam image reconstruction algorithm is reformulated utilizing mapping table in the discrete domain as: , where .

A general cone-beam reconstruction algorithm

1993 ◽  
Vol 12 (3) ◽  
pp. 486-496 ◽  
Author(s):  
G. Wang ◽  
T.-H. Lin ◽  
P. Cheng ◽  
D.M. Shinozaki
Keyword(s):  
Reconstruction Algorithm ◽  
Cone Beam ◽  
Cone Beam Reconstruction

scholarly journals 3D Analytic Cone-Beam Reconstruction for Multiaxial CT Acquisitions

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Zhye Yin ◽  
Bruno De Man ◽  
Jed Pack
Keyword(s):  
Cone Angle ◽  
Reconstruction Algorithm ◽  
Cone Beam ◽  
Multiple Sources ◽  
Relative Contribution ◽  
Cone Beam Reconstruction ◽  
Full Scan ◽  
Axial Ct ◽  
Ct System ◽  
Scan Data

A conventional 3rd generation Computed Tomography (CT) system with a single circular source trajectory is limited in terms of longitudinal scan coverage since extending the scan coverage beyond 40 mm results in significant cone-beam artifacts. A multiaxial CT acquisition is achieved by combining multiple sequential 3rd generation axial scans or by performing a single axial multisource CT scan with multiple longitudinally offset sources. Data from multiple axial scans or multiple sources provide complementary information. For full-scan acquisitions, we present a window-based 3D analytic cone-beam reconstruction algorithm by tessellating data from neighboring axial datasets. We also show that multi-axial CT acquisition can extend the axial scan coverage while minimizing cone-beam artifacts. For half-scan acquisitions, one cannot take advantage of conjugate rays. We propose a cone-angle dependent weighting approach to combine multi-axial half-scan data. We compute the relative contribution from each axial dataset to each voxel based on the X-ray beam collimation, the respective cone-angles, and the spacing between the axial scans. We present numerical experiments to demonstrate that the proposed techniques successfully reduce cone-beam artifacts at very large volumetric coverage.

Implementation of a cone-beam reconstruction algorithm for the single-circle source orbit with embedded misalignment correction using homogeneous coordinates

2001 ◽  
Vol 28 (10) ◽  
pp. 2050-2069 ◽  
Author(s):  
Marek Karolczak ◽  
Stefan Schaller ◽  
Klaus Engelke ◽  
Andreas Lutz ◽  
Ulrike Taubenreuther ◽  
...  
Keyword(s):  
Reconstruction Algorithm ◽  
Cone Beam ◽  
Homogeneous Coordinates ◽  
Cone Beam Reconstruction
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