SU-FF-T-148: Cone-Beam Reconstruction (CBR) Using a X-Ray Simulator in Intracavitary Brachytherapy

2006 ◽  
Vol 33 (6Part9) ◽  
pp. 2083-2083
Author(s):  
J Chang ◽  
T Suh ◽  
Y Ji
Keyword(s):  
Cone Beam ◽  
Intracavitary Brachytherapy ◽  
X Ray ◽  
Cone Beam Reconstruction

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

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 .

scholarly journals Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm

2011 ◽  
Vol 38 (2) ◽  
pp. 1070-1080 ◽  
Author(s):  
Damodar Pokhrel ◽  
Martin J. Murphy ◽  
Dorin A. Todor ◽  
Elisabeth Weiss ◽  
Jeffrey F. Williamson
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Intracavitary Brachytherapy ◽  
Matching Algorithm ◽  
X Ray ◽  
Forward Projection

NDT Applications of the 3D Radon Transform Algorithm for Cone Beam Reconstruction

1990 ◽  
Vol 217 ◽  
Author(s):  
P. Sire ◽  
P. Grangeat ◽  
P. Lemasson ◽  
P. Mélennec ◽  
P. Rizo
Keyword(s):  
Basic Principle ◽  
Radon Transform ◽  
Cone Beam ◽  
Imaging Processing ◽  
X Ray ◽  
First Derivative ◽  
X Ray Imaging ◽  
Cone Beam Reconstruction ◽  
Scientific Computer ◽  
Theoretical Developments

ABSTRACTThe paper describes our 3D X-ray CT algorithm “RADON” using attenuation measurements acquired with a bidimensional detector. Our inversion diagram uses the first derivative of the Radon transform synthesis then its inversion. The potentiality of that new method, particularly for the large aperture, prompted us to develop an optimized software offering convenience and high performances on a modem scientific computer. After a brief recall of the basic principle of X-ray imaging processing, we will introduce the theoretical developments resulting in the present inversion diagram. A general algorithm structure will be proposed afterwards. As a conclusion we will present the performances and the results obtained with ceramic rotors examination.

Scanning cone-beam reconstruction algorithms for x-ray microtomography

1992 ◽  
Author(s):  
Ge Wang ◽  
T. H. Lin ◽  
Ping C. Cheng ◽  
D. M. Shinozaki ◽  
Hyo-Gun Kim
Keyword(s):  
Cone Beam ◽  
Reconstruction Algorithms ◽  
X Ray ◽  
Cone Beam Reconstruction

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:

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