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Piecewise linear fitting in dynamic micro-CT

Marjolein Heyndrickx (UGent) , Matthieu Boone (UGent) , Thomas De Schryver (UGent) , Tom Bultreys (UGent) , Wannes Goethals (UGent) , Glenn Verstraete (UGent) , Valérie Vanhoorne (UGent) and Luc Van Hoorebeke (UGent)
(2018) MATERIALS CHARACTERIZATION. 139. p.259-268
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Abstract
Piecewise linear fitting, the technique proposed in this paper, performs data reduction on a large dynamic CT dataset and it already takes a step in the direction of the data analysis and characterization that needs to be performed afterwards. In addition, it drastically improves the signal-to-noise ratio. This is demonstrated on two complementary samples: a Bentheimer sandstone and a pharmaceutical tablet. This technique is developed for dynamic high-resolution CT scanning or 4D-mu CT, a tool to study dynamic processes in situ on the micro-scale. We propose to start from the low quality reconstruction and perform a piecewise linear fit in the time direction for each voxel. This effectively uses the nearby temporal information, regardless of the nature of the dynamic process, without introducing spatial correlation.
Keywords
X-ray micro-computed tomography, Analysis, Image processing, Reconstruction, Signal-to-noise ratio, X-RAY TOMOGRAPHY, COMPUTED-TOMOGRAPHY, RECONSTRUCTION ALGORITHM, IMAGE-RECONSTRUCTION, PORE, DIFFUSION, ROCK, PET

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Chicago
Heyndrickx, Marjolein, Matthieu Boone, Thomas De Schryver, Tom Bultreys, Wannes Goethals, Glenn Verstraete, Valérie Vanhoorne, and Luc Van Hoorebeke. 2018. “Piecewise Linear Fitting in Dynamic micro-CT.” Materials Characterization 139: 259–268.
APA
Heyndrickx, Marjolein, Boone, M., De Schryver, T., Bultreys, T., Goethals, W., Verstraete, G., Vanhoorne, V., et al. (2018). Piecewise linear fitting in dynamic micro-CT. MATERIALS CHARACTERIZATION, 139, 259–268.
Vancouver
1.
Heyndrickx M, Boone M, De Schryver T, Bultreys T, Goethals W, Verstraete G, et al. Piecewise linear fitting in dynamic micro-CT. MATERIALS CHARACTERIZATION. 2018;139:259–68.
MLA
Heyndrickx, Marjolein, Matthieu Boone, Thomas De Schryver, et al. “Piecewise Linear Fitting in Dynamic micro-CT.” MATERIALS CHARACTERIZATION 139 (2018): 259–268. Print.
@article{8556144,
  abstract     = {Piecewise linear fitting, the technique proposed in this paper, performs data reduction on a large dynamic CT dataset and it already takes a step in the direction of the data analysis and characterization that needs to be performed afterwards. In addition, it drastically improves the signal-to-noise ratio. This is demonstrated on two complementary samples: a Bentheimer sandstone and a pharmaceutical tablet. 
This technique is developed for dynamic high-resolution CT scanning or 4D-mu CT, a tool to study dynamic processes in situ on the micro-scale. We propose to start from the low quality reconstruction and perform a piecewise linear fit in the time direction for each voxel. This effectively uses the nearby temporal information, regardless of the nature of the dynamic process, without introducing spatial correlation.},
  author       = {Heyndrickx, Marjolein and Boone, Matthieu and De Schryver, Thomas and Bultreys, Tom and Goethals, Wannes and Verstraete, Glenn and Vanhoorne, Val{\'e}rie and Van Hoorebeke, Luc},
  issn         = {1044-5803},
  journal      = {MATERIALS CHARACTERIZATION},
  keyword      = {X-ray micro-computed tomography,Analysis,Image processing,Reconstruction,Signal-to-noise ratio,X-RAY TOMOGRAPHY,COMPUTED-TOMOGRAPHY,RECONSTRUCTION ALGORITHM,IMAGE-RECONSTRUCTION,PORE,DIFFUSION,ROCK,PET},
  language     = {eng},
  pages        = {259--268},
  title        = {Piecewise linear fitting in dynamic micro-CT},
  url          = {http://dx.doi.org/10.1016/j.matchar.2018.03.007},
  volume       = {139},
  year         = {2018},
}

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