@article{ManiKupschMuelleretal.2022,
  author    = {Mani, Deepak and Kupsch, Andreas and M{\"u}ller, Bernd R. and Bruno, Giovanni},
  title     = {Diffraction Enhanced Imaging Analysis with Pseudo-Voigt Fit Function},
  series = {Journal of imaging : open access journal},
  volume    = {8},
  journal   = {Journal of imaging : open access journal},
  number    = {8},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2313-433X},
  doi       = {10.3390/jimaging8080206},
  pages     = {13},
  year      = {2022},
  abstract  = {Diffraction enhanced imaging (DEI) is an advanced digital radiographic imaging technique employing the refraction of X-rays to contrast internal interfaces. This study aims to qualitatively and quantitatively evaluate images acquired using this technique and to assess how different fitting functions to the typical rocking curves (RCs) influence the quality of the images. RCs are obtained for every image pixel. This allows the separate determination of the absorption and the refraction properties of the material in a position-sensitive manner. Comparison of various types of fitting functions reveals that the Pseudo-Voigt (PsdV) function is best suited to fit typical RCs. A robust algorithm was developed in the Python programming language, which reliably extracts the physically meaningful information from each pixel of the image. We demonstrate the potential of the algorithm with two specimens: a silicone gel specimen that has well-defined interfaces, and an additively manufactured polycarbonate specimen.},
  language  = {en}
}