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Proceedings Paper

X-ray phase imaging and retrieval using structured illumination (Conference Presentation)
Author(s): Kaye Morgan

Paper Abstract

X-rays enable non-invasive and high-resolution imaging that has become central to medical diagnostics and security. While conventional x-ray imaging captures only strongly-attenuating materials like bone or metal, in recent years new x-ray modalities have been developed that can capture weakly-attenuating materials. In particular, variations in x-ray phase can reveal soft tissue structures like the lungs and incoherent scattering of x-rays can describe sub-pixel structures like fine powders. Most techniques that can capture these image modalities require precision optics to convert the phase and incoherent scattering effects to measurable variations in the image intensity, and use multiple exposures to separate the effects. Recent work has been able to extract the three modalities using a single exposure (enabling dynamic and low-dose imaging) and without the need for precision optics (reducing the cost of a set-up). This is possible using structured x-ray illumination and post-measurement computational analysis. The x-ray illumination can be either a grid-like periodic pattern [1,2], or a completely random pattern, such as the pattern produced when a piece of sandpaper is placed in the x-ray beam [3]. Local shifts in the illumination pattern result from x-ray phase variations, and a ‘blurring-out’ of the illumination pattern indicates the presence of sub-pixel structures that scatter the x-ray light. This talk will describe these new methods of x-ray imaging, touching on mathematical models that predict the wavefield behavior, methods of computational analysis and applications to biomedical research [4]. [1] K. Morgan, T. Petersen, M. Donnelley, et al., Optics Express 24 (2016). [2] K. Morgan, P. Modregger, S. Irvine, et al., Optics Letters, 38 (2013). [3] K. Morgan, D. Paganin and K. Siu, Applied Physics Letters 100 (2012). [4] K. Morgan, M. Donnelley, N. Farrow et al., AJRCCM 190 (2014).

Paper Details

Date Published: 13 May 2019
Proc. SPIE 10990, Computational Imaging IV, 109900T (13 May 2019); doi: 10.1117/12.2520826
Show Author Affiliations
Kaye Morgan, Monash Univ. (Australia)

Published in SPIE Proceedings Vol. 10990:
Computational Imaging IV
Abhijit Mahalanobis; Lei Tian; Jonathan C. Petruccelli, Editor(s)

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