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Optimizing and applying high‐resolution, in‐line laboratory phase‐contrast X‐ray imaging for low‐density material samples
Author(s) -
Zboray Robert
Publication year - 2021
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/jmi.12986
Subject(s) - attenuation , scanner , image quality , phase contrast imaging , phase retrieval , image resolution , optics , detector , materials science , contrast (vision) , phase (matter) , contrast to noise ratio , noise (video) , focus (optics) , resolution (logic) , sensitivity (control systems) , computer science , artificial intelligence , physics , image (mathematics) , phase contrast microscopy , electronic engineering , fourier transform , quantum mechanics , engineering
In‐line, or propagation‐based phase‐contrast X‐ray imaging (PBI) is an attractive alternative to the attenuation‐based modality for low‐density, soft samples showing low attenuation contrast. With the growing availability of micro‐ and nano‐focus X‐ray tubes, the method is increasingly applied in the laboratory. Here, we discuss the technique and demonstrate its advantages for selected low‐density, low attenuation material samples using a lab‐based micro‐ and nano‐computed tomography systems Easytom XL Ultra, providing micron and sub‐micron range resolution PBI images. We demonstrate a multi‐step optimization of the lab‐based PBI technique on our scanner that includes choosing the optimal detector‐source hardware combination available in the setup, then optimizing the imaging geometry and finally the phase retrieval process through a parametric study. We point out and elaborate on the effect of noise correlation and texturing due to phase retrieval. We demonstrate the overall benefits of using the phase image and the phase retrieval for the selected samples such as improved image quality, increased contrast‐to‐noise ratio while only marginally influencing the spatial resolution. The improvement in image quality also enables further image processing steps for detailed structural analysis of the samples, which would be much more complicated if not impossible based on the transmission image.