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2022
DOI: 10.1088/1748-0221/17/10/p10030
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Sub-pixel energy-weighting techniques for metallic contaminant highlighting in a pharmaceutical hard capsule using a Timepix3 CdZnTe hybrid pixel detector

Abstract: The presented work describes the capabilities of a state-of-the-art spectroscopic photon-counting hybrid pixel detector for use in non-destructive testing, as a contaminant detector with potential uses in the food and pharmaceutical industries. A pharmaceutical hard capsule containing vitamin powder, contaminated with Steel (ST) and Tungsten (W) was prepared under controlled conditions. Both contaminants are distinguished from the powder by combining sub-pixel imaging with spectroscopic imaging a… Show more

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Cited by 6 publications
(8 citation statements)
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“…On the right side, the material segmentation (black area for steel, gray for coffee and white for plastics) performed on low charge sharing images (G-CSD and CSD images) was in agreement with the ground-truth segmentation; meanwhile, poor segmentation was obtained in the raw images. To quantify the image quality enhancements, we used the well-known contrast-to-noise ratio ( CNR ) [ 6 , 7 , 8 ] as figure of merit, calculated for each ROI selected by the segmentation, as follows: where, I C and I B are the average normalized intensities of the selected contaminant (steel or plastics) and background (coffee), respectively, while σ B is the standard deviation of the background and C C the contrast. The CNR gave a good quantification of the contributes of both contrast and noise in the images.…”
Section: Energy-resolved Images and Contrast Enhancements In A Food S...mentioning
confidence: 99%
See 4 more Smart Citations
“…On the right side, the material segmentation (black area for steel, gray for coffee and white for plastics) performed on low charge sharing images (G-CSD and CSD images) was in agreement with the ground-truth segmentation; meanwhile, poor segmentation was obtained in the raw images. To quantify the image quality enhancements, we used the well-known contrast-to-noise ratio ( CNR ) [ 6 , 7 , 8 ] as figure of merit, calculated for each ROI selected by the segmentation, as follows: where, I C and I B are the average normalized intensities of the selected contaminant (steel or plastics) and background (coffee), respectively, while σ B is the standard deviation of the background and C C the contrast. The CNR gave a good quantification of the contributes of both contrast and noise in the images.…”
Section: Energy-resolved Images and Contrast Enhancements In A Food S...mentioning
confidence: 99%
“…The CNR gave a good quantification of the contributes of both contrast and noise in the images. Typically, a CNR ranging between 3–5 is required for an object to be considered detectable [ 6 , 7 , 8 ].…”
Section: Energy-resolved Images and Contrast Enhancements In A Food S...mentioning
confidence: 99%
See 3 more Smart Citations