A Multiple Cone-Beam Reconstruction Algorithm for X-Ray Microtomography

1992 ◽  
pp. 296-300 ◽  
Author(s):  
T. H. Lin ◽  
G. Wang ◽  
P. C. Cheng
Keyword(s):  
Reconstruction Algorithm ◽  
Cone Beam ◽  
X Ray ◽  
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 .

Cone-beam 3D image reconstruction in x-ray microtomography

1993 ◽  
Vol 51 ◽  
pp. 654-655
Author(s):  
G. Wang ◽  
P. C. Cheng ◽  
T. H. Lin ◽  
D. M. Shinozaki ◽  
H. Kim
Keyword(s):  
Image Reconstruction ◽  
Point Source ◽  
Reconstruction Algorithm ◽  
Cone Beam ◽  
X Rays ◽  
Reconstruction Algorithms ◽  
X Ray ◽  
3D Image Reconstruction ◽  
Cone Beam Reconstruction ◽  
Mechanical Stage

An X-ray shadow projection microscope system using a scannable point source of X-rays is under development at AMIL-ARTS, SUNY at Buffalo, USA. The point source is generated by a focussed electron beam, which can be steered electromagnetically in a plane perpendicular to the optical axis of the microscope. A specimen is mounted on a rotatable mechanical stage for microtomography. Considering the hardware characteristics of this system and the limitations of current cone-beam reconstruction algorithms, a generalized Feldkamp’s cone-beam image reconstruction algorithm has been developed at our laboratories. In our cone-beam reconstruction, there are mainly two kinds of scanning scanning modes: planar and helix-like. A planar scanning locus is used to handle spherical or plate-like specimens. A typical case of planar scanning loci is a circle, which is used in Feldkamp’s cone-beam reconstruction. A helix-like scanning locus is used to deal with rod-shaped specimens. Without loss of generality, a locus turn of the X-ray source can be defined in cylindrical coordinates by the following equation:

X-ray micro-CT with a displaced detector array: Application to helical cone-beam reconstruction

2003 ◽  
Vol 30 (10) ◽  
pp. 2758-2761 ◽  
Author(s):  
Vinson Liu ◽  
Nicholas R. Lariviere ◽  
Ge Wang
Keyword(s):  
Detector Array ◽  
Cone Beam ◽  
Micro Ct ◽  
X Ray ◽  
Cone Beam Reconstruction

Reconstruction Algorithm of Cone-Beam Phase X-Ray Computer-Tomography Based on Grating Imaging

2008 ◽  
Vol 28 (6) ◽  
pp. 1079-1084
Author(s):  
陈欣 Chen Xin ◽  
孙怡 Sun Yi ◽  
朱佩平 Zhu Peiping
Keyword(s):  
Computer Tomography ◽  
Reconstruction Algorithm ◽  
Cone Beam ◽  
X Ray

Reconstruction Algorithm for Cone-Beam X-Ray CT Using Inverse Filtering

1990 ◽  
Vol 21 (3) ◽  
pp. 25-34
Author(s):  
Hiroshi Matsuo ◽  
Aklra Iwata ◽  
Nobuo Suzumura ◽  
Isao Horiba
Keyword(s):  
Reconstruction Algorithm ◽  
Cone Beam ◽  
Inverse Filtering ◽  
X Ray

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.

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