Interface for Semi-automatic Image Contrast Enhancement in the Propagation-based X-ray Phase Contrast Method
| Authors | A.V. Polishchuk1, M.O. Pavlyuk1,2, A.V. Tarasenko2, V.V. Zhurakulov2 |
| Affiliations |
1Institute of Applied Physics of the National Academy of Sciences of Ukraine, 58, Petropavlivska Str., 40000 Sumy, Ukraine 2Sumy State University, 2, Rimsky Korsakov Str., 40007 Sumy, Ukraine |
| Е-mail | polishukav@ipfcentr.sumy.ua |
| Issue | Volume 15, Year 2023, Number 4 |
| Dates | Received 06 March 2023, revised manuscript received 17 August 2023, published online 30 August 2023 |
| Citation | A.V. Polishchuk, M.O. Pavlyuk, et al., J. Nano- Electron. Phys. 15 No 4, 04037 (2023) |
| DOI | https://doi.org/10.21272/jnep.15(4).04037 |
| PACS Number(s) | 07.05.Pj, 87.64.mh, 42.30.Wb 87.59.e, 07.05.Wr, 29.50.v |
| Keywords | Matlab (7) , Semi-automatic, Interface (7) , Normalization, X-ray phase-contrast imaging, Software environment, Mathematical modeling (7) . |
| Annotation |
This paper describes a graphical user interface developed for the normalization of radiograms and semi-automatic search for the most contrast images using a given reference, the experimental data for which were obtained using the analytical technique of X-ray phase contrast imaging. The projections of the biological object were obtained by applying free space propagation of coherent radiation when no additional optical elements are placed between the sample and the detector equipped with a YAG:Ce scintillator to exploit the interference effects characteristic of the method due to the high-intensity characteristics of the X-ray light of the SOLEIL synchrotron. The energy of the X-ray photons was 10 keV, and the distance between the sample and the detector was 16.5 cm. We consider the use of standard Matlab tools for algorithmic correction of inhomogeneities of the detector and probing light beam used to build an image of the internal structure of the object and to evaluate the contrast of a group of images, by choosing such common quality criteria as PSNR and SSIM. The program is able to generate such a set of images depending on the parameters entered by the user for a subjective search for contrast images. Numerical estimates well confirm the visual results of the algorithmic search and allow us to reach the most informative image from the generated array, which is created by the user using the interface. The aim of this work is to familiarize with the use of the developed software product and the concept of semi-automatic search among the dataset of digital phase-contrast images. |
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