| Autor: |
M.J. Pankhurst, R. Fowler, L. Courtois, S. Nonni, F. Zuddas, R.C. Atwood, G.R. Davis, P.D. Lee |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
SoftwareX, Vol 7, Iss , Pp 115-121 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2352-7110 |
| DOI: |
10.1016/j.softx.2018.03.004 |
| Popis: |
We present new software allowing significantly improved quantitative mapping of the three-dimensional density distribution of objects using laboratory source polychromatic X-rays via a beam characterisation approach (c.f. filtering or comparison to phantoms). One key advantage is that a precise representation of the specimen material is not required. The method exploits well-established, widely available, non-destructive and increasingly accessible laboratory-source X-ray tomography. Beam characterisation is performed in two stages: (1) projection data are collected through a range of known materials utilising a novel hardware design integrated into the rotation stage; and (2) a Python code optimises a spectral response model of the system. We provide hardware designs for use with a rotation stage able to be tilted, yet the concept is easily adaptable to virtually any laboratory system and sample, and implicitly corrects the image artefact known as beam hardening. Keywords: Laboratory X-ray micro-computed tomography, Beam characterisation, Python, Beam hardening, Three-dimensional densitometry |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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