| 1. |
- Van den Bulcke, Jan, et al.
(author)
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3D tree-ring analysis using helical X-ray tomography
- 2014
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In: Dendrochronologia. - : Elsevier BV. - 1125-7865 .- 1612-0051. ; 32:1, s. 39-46
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Journal article (peer-reviewed)abstract
- The current state-of-the-art of tree-ring analysis and densitometry is still mainly limited to two dimensions and mostly requires proper treatment of the surface of the samples. In this paper we elaborate on the potential of helical X-ray computed tomography for 3D tree-ring analysis. Microdensitometrical profiles are obtained by processing of the reconstructed volumes. Correction of the structure direction, taking into account the angle of growth rings and grain, results in very accurate microdensity and precise ring width measurements. Both a manual as well as an automated methodology is proposed here, of which the MATLAB (c) code is available. Examples are given for pine (Pinus sylvestris L), oak (Quercus robur L) and teak (Tectona grandis L.). In all, the methodologies applied here on the 3D volumes are useful for growth related studies, enabling a fast and non-destructive analysis.
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| 2. |
- Wernersson, Erik L. G., et al.
(author)
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Postprocessing method for reducing phase effects in reconstructed microcomputed-tomography data
- 2013
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In: Optical Society of America. Journal A. - 1084-7529 .- 1520-8532. ; 30:3, s. 455-461
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Journal article (peer-reviewed)abstract
- With increased resolution in x-ray computed tomography, refraction adds increasingly to the attenuation signal. Though potentially beneficial, the artifacts caused by refraction often need to be removed from the image. In this paper, we propose a postprocessing method, based on deconvolution, that is able to remove these artifacts after conventional reconstruction. This method poses two advantages over existing projection-based (preprocessing) phase-retrieval or phase-removal algorithms. First, evaluation of the parameters can be done very quickly, improving the overall speed of the method. Second, postprocessing methods can be applied when projection data is not available, which occurs in several commercial systems with closed software or when projection data has been deleted. It is shown that the proposed method performs comparably to state-of-the-art methods in terms of image quality.
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