SU-FF-I-116: Estimation of Imaging Geometry Parameters of a Multiple Source Digital Tomosynthesis System Using a Standard Cone Beam CT Calibration Phantom

2009 ◽  
Vol 36 (6Part4) ◽  
pp. 2461-2461
Author(s):  
A Paidi ◽  
S Bose ◽  
J Maltz ◽  
A Bani-Hashemi
Keyword(s):  
Cone Beam Ct ◽  
Multiple Source ◽  
Cone Beam ◽  
Digital Tomosynthesis ◽  
Imaging Geometry ◽  
Calibration Phantom

Simultaneous calibration phantom commission and geometry calibration in cone beam CT

2017 ◽  
Vol 62 (17) ◽  
pp. N375-N390 ◽  
Author(s):  
Yuan Xu ◽  
Shuai Yang ◽  
Jianhui Ma ◽  
Bin Li ◽  
Shuyu Wu ◽  
...  
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Calibration Phantom ◽  
Geometry Calibration

scholarly journals Digital Tomosynthesis-Guided Bronchoscopy Followed by Cone Beam CT: The Vanderbilt Experience

2020 ◽  
Author(s):  
J. Katsis ◽  
M.G. Lester ◽  
L. Roller ◽  
R.J. Lentz ◽  
O.B. Rickman ◽  
...  
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Digital Tomosynthesis

scholarly journals Comparing Digital Tomosynthesis to Cone-Beam CT for Position Verification in Patients Undergoing Partial Breast Irradiation

2009 ◽  
Vol 73 (3) ◽  
pp. 952-957 ◽  
Author(s):  
Junan Zhang ◽  
Q. Jackie Wu ◽  
Devon J. Godfrey ◽  
Toyosi Fatunase ◽  
Lawrence B. Marks ◽  
...  
Keyword(s):  
Cone Beam Ct ◽  
Cone Beam ◽  
Partial Breast Irradiation ◽  
Digital Tomosynthesis ◽  
Breast Irradiation

Design criteria for geometrical calibration phantoms in fan and cone beam CT systems

2018 ◽  
Vol 26 (6) ◽  
pp. 729-753
Author(s):  
Peter Jonas
Keyword(s):  
Numerical Method ◽  
Cone Beam Ct ◽  
Sufficient Conditions ◽  
Cone Beam ◽  
Geometrical Parameters ◽  
Main Question ◽  
X Ray ◽  
Precise Knowledge ◽  
Calibration Phantom ◽  
Geometrical Data

Abstract Image quality in tomographic applications depends strongly on the precise knowledge of the geometrical parameters of x-ray source and detector. However, in some situations these geometrical data are not immediately available. One way to overcome this problem is to use calibration phantoms which consist of several opaque markers in a known geometry. A main question is what properties are needed in order to reliably determine the searched for geometry data. In this paper we give sufficient conditions for the calibration phantom such that the reconstruction problem has a unique solution. We also use our theoretical approach to derive a numerical method which can determine the needed geometry data. Our analyses show that this numerical method is stable and that the solutions are as good as those of standard nonlinear procedures like Gauss–Newton-type methods. Furthermore, our new algorithm is much faster than standard methods and it also does not depend on initial values.

Sign in / Sign up

Export Citation Format

Share Document