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Fast, non-iterative algorithm for quantitative integration of X-ray differential phase-contrast images
Author(s) -
Lorenzo Massimi,
Ian Buchanan,
Alberto Astolfo,
Marco Endrizzi,
Alessandro Olivo
Publication year - 2020
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.405755
Subject(s) - computer science , phase retrieval , phase (matter) , pixel , algorithm , filter (signal processing) , optics , image quality , phase contrast imaging , contrast (vision) , noise (video) , differential (mechanical device) , image processing , artificial intelligence , computer vision , image (mathematics) , mathematics , fourier transform , physics , phase contrast microscopy , mathematical analysis , quantum mechanics , thermodynamics
X-ray phase contrast imaging is gaining importance as an imaging tool. However, it is common for X-ray phase detection techniques to be sensitive to the derivatives of the phase. Therefore, the integration of differential phase images is a fundamental step both to access quantitative pixel content and for further analysis such as segmentation. The integration of noisy data leads to artefacts with a severe impact on image quality and on its quantitative content. In this work, an integration method based on the Wiener filter is presented and tested using simulated and real data obtained with the edge illumination differential X-ray phase imaging method. The method is shown to provide high image quality while preserving the quantitative pixel content of the integrated image. In addition, it requires a short computational time making it suitable for large datasets.

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