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Quantitative dual-energy micro-CT with a photon-counting detector for material science and non-destructive testing
- Source :
- PLoS ONE, PLoS ONE, Vol 14, Iss 7, p e0219659 (2019)
- Publication Year :
- 2019
-
Abstract
- The recent progress in photon-counting detector technology using high-Z semiconductor sensors provides new possibilities for spectral x-ray imaging. The benefits of the approach to extract spectral information directly from measurements in the projection domain are very advantageous for material science studies with x-rays as polychromatic artifacts like beam-hardening are handled properly. Since related methods require accurate knowledge of all energy-dependent system parameters, we utilize an adapted semi-empirical model, which relies on a simple calibration procedure. The method enables a projection-based decomposition of photon-counting raw-data into basis material projections. The objective of this paper is to investigate the method's performance applied to x-ray micro-CT with special focus on applications in material science and non-destructive testing. Projection-based dual-energy micro-CT is shown to be of good quantitative accuracy regarding material properties such as electron densities and effective atomic numbers. Furthermore, we show that the proposed approach strongly reduces beam-hardening artifacts and improves image contrast at constant measurement time.
- Subjects :
- Imaging Techniques
Science
Image Processing
Materials Science
Electrons
Neuroimaging
Research and Analysis Methods
Diagnostic Radiology
Diagnostic Medicine
Image Processing, Computer-Assisted
Medicine and Health Sciences
Electron Density
Particle Physics
Tomography
Titanium
Photons
Phantoms, Imaging
Radiology and Imaging
Physics
Reproducibility of Results
Biology and Life Sciences
Equipment Design
X-Ray Microtomography
Models, Theoretical
Condensed Matter Physics
Bone Imaging
Computed Axial Tomography
X-Ray Radiography
Chemistry
Calibration
Physical Sciences
Signal Processing
Medicine
Engineering and Technology
Artifacts
Algorithms
Elementary Particles
Research Article
Neuroscience
Chemical Elements
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 14
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.pmid.dedup....dae75e436ce80ba1ff713c5d2eeeffd8