Mani Deepak, Kupsch Andreas, Müller Bernd R, Bruno Giovanni
Bundesanstalt für Materialforschung und -Prüfung (BAM), Unter den Eichen 87, 12205 Berlin, Germany.
Non-Destructive Testing Int., Engineering Department, Dresden International University (DIU), Freiberger Str. 37, 01067 Dresden, Germany.
J Imaging. 2022 Jul 23;8(8):206. doi: 10.3390/jimaging8080206.
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.
衍射增强成像（DEI）是一种先进的数字射线成像技术，它利用X射线的折射来突出内部界面的对比度。本研究旨在对使用该技术获取的图像进行定性和定量评估，并评估对典型摇摆曲线（RCs）采用不同的拟合函数如何影响图像质量。针对每个图像像素获取RCs。这使得能够以位置敏感的方式分别确定材料的吸收和折射特性。对各种类型拟合函数的比较表明，伪沃伊特（PsdV）函数最适合拟合典型的RCs。用Python编程语言开发了一种强大的算法，该算法能可靠地从图像的每个像素中提取物理上有意义的信息。我们用两个样本展示了该算法的潜力：一个具有清晰界定界面的硅胶样本和一个增材制造的聚碳酸酯样本。
