Recovering refraction and attenuation information in an unknown sample using x-ray propagation-based phase-contrast tomography

Phase-contrast X-ray imaging (PCXI) techniques employ both X-ray refraction and attenuation to generate image contrast, and are therefore capable of forming high-quality images of weakly attenuating samples, for example, soft-tissues in mammography. Propagation-based phase-contrast X-ray imaging (PB...

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Hauptverfasser: Alloo, S. J., Croton, L. C. P., Kitchen, M. J., Paganin, D. M., Morgan, K. S., Nesterets, Ya. I., Mohammadi, S., Lockie, D., Menk, R. H., Arfelli, F., Zanconati, F., Dullin, C., Tromba, G., Pavlov, K. M.
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Phase-contrast X-ray imaging (PCXI) techniques employ both X-ray refraction and attenuation to generate image contrast, and are therefore capable of forming high-quality images of weakly attenuating samples, for example, soft-tissues in mammography. Propagation-based phase-contrast X-ray imaging (PB-PCXI) is an especially simple PCXI technique as it requires no additional precision optics in the experimental set-up, and hence can be easily implemented in numerous disciplines. We recently published a PB-PCXI algorithm capable of extracting the real, δ, and imaginary, β, refractive index components of composite materials within an unknown sample [1]. This was previously applied to PB-PCXI data collected using a synchrotron facility where the X-ray wavefield was monochromatic, highly coherent, and paraxial. Within this work, we have validated, and further extended, this approach by applying it to PB-PCXI data collected using a conventional laboratory X-ray source that produces a polychromatic, relatively temporally incoherent and divergent wavefield. We demonstrate that our previously published phase and attenuation extraction algorithm can be applied to biological tissue sample data collected using such a laboratory X-ray source, thereby broadening the applicability of this algorithm. A link to a repository is provided, where a Python3 script implementing this approach can be downloaded.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0168155