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Therefore, it was pre-treated by a Matlab script to segment the dense material prior to the beam hardening correction.
This difference in values might be due to the over estimate of the gray values threshold that we selected for celestite prior to the beam hardening correction.
We present tomographic studies on 10B enriched steels and compare different reconstruction techniques, the filtered backprojection with and without beam hardening correction, and the maximum-likelihood method.
A beam hardening correction was done for relevant radiograms and an iterative OSEM (ordered subsets) method was applied for CT reconstructions.
The bright grey values for celestite, by contrast with other components of the porous material, induced artifacts during the beam hardening correction of the high resolution data set (5.89 µm voxel size).
Reconstruction of sections was done using a modified Feldkamp cone-beam algorithm, with the beam hardening correction set to 50%.
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Beam-hardening correction is inherent in this process, and image noise reduction is addressed in the reconstruction chain.
Therefore, beam-hardening artifact correction for coronary CT imaging is essential for accurate assessment of myocardial perfusion imaging.
However, beam-hardening artifacts cannot be completely eliminated using the current beam-hardening correction algorithms [ 74].
Recent study shows that image-based beam-hardening correction algorithm is feasible for the correction of beam-hardening artifacts that mimic perfusion defects.
The beam-hardening correction used in the study was an image-based correction algorithm that enables individual estimation of the beam hardening from high-enhancing material and water-enhancing material for accurate calculation of the amount of beam hardening and to reconstruct a corrected image [ 74, 75].
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