scholarly journals Deep learning based spectral extrapolation for dual‐source, dual‐energy x‐ray computed tomography

2020 ◽  
Vol 47 (9) ◽  
pp. 4150-4163
Author(s):  
Darin P. Clark ◽  
Fides R. Schwartz ◽  
Daniele Marin ◽  
Juan C. Ramirez‐Giraldo ◽  
Cristian T. Badea
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Dual Energy ◽  
X Ray ◽  
Dual Source ◽  
X Ray Computed

Applications of Dual-Energy X-ray Computed Tomography to Structural Ceramics*

1988 ◽  
Vol 32 ◽  
pp. 629-640
Author(s):  
W. A. Ellingson ◽  
M. W. Vannier
Keyword(s):  
Computed Tomography ◽  
Evaluation Method ◽  
Combustion Engine ◽  
Mass Density ◽  
Energy Levels ◽  
Dual Energy ◽  
Structural Ceramics ◽  
X Ray ◽  
X Ray Computed ◽  
Engine Components

AbstractAdvanced structural ceramics (Si3N4, SiC, A12O3, ZrO2) are rapidly being developed with sufficient fracture toughness to be considered for engineering applications such as internal combustion engine components, rotating turbine engine components, and heat recovery systems. X-ray computed tomography (CT) is a promising nondestructive evaluation method for these ceramics, but beam hardening presents a serious problem in the interpretation of CT images generated with polychromatic X-ray sources by creating artifacts . Dual-energy X-ray techniques have the potential to eliminate these problems. In addition, in theory, dual energy allows generation of quasimonochromatic equivalent images, which should allow verification of theoretically determined optimum energies. In using dual-energy methods, the high-and low-energy images are nonlinearly transformed to generate two energy-independent images characterizing the integrated Compton/photoelectric attenuation components. Characteristic linear combinations of these two "basis" images can serve to identify unknown materials and generate synthesized monoenergetic images.The dual-energy method has been used to study structural ceramics as well as liquids that are close to ceramic materials in atomic number and mass density. The work was done on a Siemens DR-H CT machine with 85- and 125-kVp energy levels. Test samples included Si3N4 cylinders ranging from 10 to 50 mm in diameter, liquid Freon TF, and densified SiC.

Design of a nanoprobe for high field magnetic resonance imaging, dual energy X-ray computed tomography and luminescent imaging

2020 ◽  
Vol 573 ◽  
pp. 278-286 ◽  
Author(s):  
Daniel González-Mancebo ◽  
Ana Isabel Becerro ◽  
Ariadna Corral ◽  
Sonia García-Embid ◽  
Marcin Balcerzyk ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
Magnetic Resonance ◽  
High Field ◽  
Dual Energy ◽  
Resonance Imaging ◽  
X Ray ◽  
X Ray Computed

Dual-energy X-ray computed tomography for void detection in fiber-reinforced composites

2019 ◽  
Vol 53 (17) ◽  
pp. 2349-2359 ◽  
Author(s):  
Yasuhito Suzuki ◽  
Dylan S Cousins ◽  
John R Dorgan ◽  
Aaron P Stebner ◽  
Branden B Kappes
Keyword(s):  
Computed Tomography ◽  
Dual Energy ◽  
Fiber Reinforced Composites ◽  
Reinforced Composites ◽  
Fiber Reinforced ◽  
X Ray ◽  
Void Detection ◽  
X Ray Computed

Adopting Traditional Image Algorithms and Deep Learning to Build the Finite Model of a 2.5D Composite Based on X-Ray Computed Tomography

2021 ◽  
pp. 114440
Author(s):  
Yunfa Jia ◽  
Guoqiang Yu ◽  
Jinkang Du ◽  
Xiguang Gao ◽  
Yingdong Song ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Finite Model ◽  
X Ray ◽  
X Ray Computed ◽  
Traditional Image

Features of dual-energy X-ray computed tomography

2005 ◽  
Vol 548 (1-2) ◽  
pp. 99-105 ◽  
Author(s):  
M. Torikoshi ◽  
T. Tsunoo ◽  
Y. Ohno ◽  
M. Endo ◽  
M. Natsuhori ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Dual Energy ◽  
X Ray ◽  
X Ray Computed
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