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Träfflista för sökning "WFRF:(O'Nils Mattias) ;pers:(Norlin Börje 1967)"

Sökning: WFRF:(O'Nils Mattias) > Norlin Börje 1967

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1.
  • Norlin, Börje, 1967-, et al. (författare)
  • Energy Resolved X-ray Imaging as a Tool for Characterization of Paper Coating Quality
  • 2009
  • Ingår i: IEEE Nuclear Science Symposium Conference Record 2009. - : IEEE conference proceedings. - 9781424439621 ; , s. 1703-1706
  • Konferensbidrag (refereegranskat)abstract
    • Energy resolved X-ray imaging can be used as a tool to analyze the variation in the chemical content of an object. In this work we have used energy resolved X-ray imaging to measure the variation in the chemical content of paper and paper coating. This is an important quality parameter for the paper industry. In order to separate the variation in coating thickness from the variation in paper thickness, energy resolution is used to separate the response of the coating from the response of the paper. The MEDIPIX2 single photon processing X-ray imaging system [1] has been used in the measurements.  The measurement results are compared to simulations with MCNP. The influence of charge sharing is discussed and the effects have been studied by comparing results from detectors with 220x220 µm2 pixels and detectors with 55x55 µm2 pixels. There is a trade-off between good spatial resolution obtained with detectors with small pixels and good energy resolution obtained with detectors with large pixels. The requirements on image quality, to achieve the resolution of coating distribution relevant for the application, are discussed.
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2.
  • O'Nils, Mattias, 1969-, et al. (författare)
  • Threshold Modulation for Continuous Energy Resolution with Two Channels per Pixel in a Photon Counting X-ray Image Detector
  • 2009
  • Ingår i: Nuclear Instruments and Methods in Physics Research Section A. - : Elsevier. - 0168-9002 .- 1872-9576. ; 607:1, s. 236-239
  • Tidskriftsartikel (refereegranskat)abstract
    • The introduction of energy resolution in X-ray image detectors will lead to tradeoffs between circuit complexity and spatial/energy resolution in the pixel design. The proposed method provides continuous energy resolution with only two energy channels per pixel, which is a comparable complexity to that of a window discriminator pixel like Medipix2. The paper illustrates the method and validates the method through analytical analysis and through simulation of real and synthetic data.
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3.
  • Thim, Jan, et al. (författare)
  • Realizing increased sub-pixel spatial resolution in X-ray imaging using displaced multiple images
  • 2009
  • Ingår i: 11th International Workshop on Radiation Imaging Detectors.
  • Konferensbidrag (refereegranskat)abstract
    • In X-Ray imaging with pixel detector systems, the resolution of the image taken is dependant on the pixel size in the detector readout electronics. Depending on the functionality of the readout electronics, the surface space on the readout chip for each pixel has a minimum size, which sets the spatial resolution of the taken images. For applications where it is required to image extremely small structures in a material, the spatial resolution of the X-Ray detector system sets the limit, and readout systems with high functionality cannot be considered. One way to reach sub-pixel resolution is to use a nanofocus source to achieve an X-ray microscopy setup [1]. However, this type of X-ray source is still too expensive to be an alternative for quality assurance systems used in the industry. In this paper we focus on a much simpler way of increasing spatial resolution that has proven effective in images for visible light. By mounting either the objects for imaging or the image sensor system on a step motor table and take multiple images slightly dislocated from one another, an increase in sub-pixel spatial resolution can be achieved. Consider the case that an image sensor system with a pixel size of 55x55 µm is available for an imaging application that requires a resolution of 20x20 µm. The application is material characterization and allows for multiple images to be taken for one sample. In this case, increasing the sub-pixel resolution by nine times (3x3) will result in a pixel size of about 18x18 µm, which would meet the requirements. This can be realized by taking nine images dislocated 1/3 of the pixel width from each other. If the upper left pixel of the centre image has coordinates (0,0) the upper left pixel of all the nine images will have coordinates (-1/3,1/3), (0,1/3), (1/3,1/3), (-1/3,0), (0,0), (1/3,0), (-1/3,-1/3), (0,-1/3) and (1/3,-1/3). The result of a direct combination of these images is illustrated in Figure 1, where one of nine images is shown at the left. Combining the images without images processing with an algorithm will yield the image in the centre, which can be compared to how the image would look in full 9x resolution (right image). As can be seen, some details are lost and the image is blurred compared to a full resolution image. However, with an image processing algorithm in the combination phase this effect can be reduced and the image quality increased. This paper shows simulated and measured results from using dislocation imaging in X-Ray imaging systems, where the test case system will be the MEDIPIX2 system [2]. An investigation of different image processing algorithms suitable for this type of imaging is conducted. An investigation is also done to show whether detectors with large size pixels compared to the standard size in a MEDIPIX system can be combined with the described sub-pixel scaling technique. The result of this combination is used to investigate the charge sharing effects on the MEDIPIX system. [1] Norlin B., Fröjdh C., Nuclear Instruments and Methods, sect. A (2009), doi:10.1016/j.nima.2009.03.155[2] Llopart X., Campbell M., Dinapoli R., san Segundo D., Pernigotti E., IEEE Transactions on Nuclear Science, Vol. 49, Issue 5, Part 1, pp. 2279-2283, October 2002. Figure 1. Image (left) with 50x50 pixels, with the resulting combination of nine images forming an image with a sub-pixel resolution of 150x150 pixel (centre), compared to a full resolution reference image (right).
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