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Investigation on the Dependency of Phase Retrieval Accuracy Versus Edge Enhancement to the Noise Ratio of X-ray Propagation-Based Phase-Contrast Imaging

Published online by Cambridge University Press:  13 August 2019

Lin Zhang ,
Huijuan Zhao ,
Jingying Jiang ,
Limin Zhang ,
Jiao Li ,
Feng Gao  and
Zhongxing Zhou
Lin Zhang
Affiliation:
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China
Huijuan Zhao
Affiliation:
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, People's Republic of China
Jingying Jiang*
Affiliation:
Beijing Advanced Innovation Centre for Big Data-based Precision Medicine, Beihang University, Beijing 100191, China
Limin Zhang
Affiliation:
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, People's Republic of China
Jiao Li
Affiliation:
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, People's Republic of China
Feng Gao
Affiliation:
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, People's Republic of China
Zhongxing Zhou*
Affiliation:
School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, People's Republic of China Tianjin Key Laboratory of Biomedical Detecting Techniques and Instruments, Tianjin, People's Republic of China Tianjin Shareshine Technology Development Co, Ltd., Tianjin, People's Republic of China Tianjin Key Laboratory in Environmental Monitoring Techniques, Tianjin, People's Republic of China
*
*Author for correspondence: Zhongxing Zhou, E-mail: zhouzhongxing@tju.edu.cn; Jingying Jiang, E-mail: jingyingjiang@buua.edu.cn
*Author for correspondence: Zhongxing Zhou, E-mail: zhouzhongxing@tju.edu.cn; Jingying Jiang, E-mail: jingyingjiang@buua.edu.cn
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Abstract

Phase retrieval is necessary for propagation-based phase-contrast imaging (PB-PCI). Arhatari established a model for predicting the impact of the sample-to-detector distance and the system noise on the phase retrieval performance. We have extended Arhatari's model to account for the parameters of excessive source size, finite detector resolution, and geometrical magnification for more practical cases. However, there exist interaction effects among these parameters resulting in difficulty of predicting the phase retrieval performance. In this study, we found that optimizing the trade-off among these parameters for phase retrieval is consistent with the improvement of edge enhancement to noise ratio (EE/N) in the “forward problem” of the PB-PCI. Hence, we engaged in establishing a relationship between EE/N and phase retrieval performance in terms of the “forward problem” and “inverse problem” of the PB-PCI, respectively. Our results showed that, at fixed detector resolution, phase retrieval from the phase-contrast projections at the same EE/N level resulted in the consistent phase retrieval performance. Therefore, the performance of phase retrieval can be predicted based on the EE/N level and be quantitatively optimized by increasing EE/N.

Keywords

EE/Nforward and inverse modeloptimizationPB-PCIphase retrieval
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 25 , Issue 5 , October 2019 , pp. 1201 - 1212
Copyright
Copyright © Microscopy Society of America 2019 

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References

Arhatari, BD, Gates, WP, Eshtiaghi, N & Peele, AG (2010). Phase retrieval tomography in the presence of noise. J Appl Phys 107, 034904.Google Scholar
Arhatari, BD & Peele, AG (2010). Optimisation of phase imaging geometry. Opt Express 18, 23727–23739.Google Scholar
Balles, A, Zabler, S, Ebensperger, T, Fella, C & Hanke, R (2016). Propagator based formalism for optimizing in-line phase contrast imaging in laboratory X-ray setups. Rev Sci Instrum 87, 093707.Google Scholar
Baran, P, Pacilè, S, Nesterets, YI, Mayo, SC, Dullin, C, Dreossi, D, Arfelli, F, Thompson, D, Lockie, D, McCormack, M, Taba, ST, Brun, F, Pinamonti, M, Nickson, C, Hall, C, Dimmock, M, Zanconati, F, Cholewa, M, Quiney, H, Brennan, PC, Tromba, G & Gureyev, TE (2017). Optimization of propagation-based x-ray phase-contrast tomography for breast cancer imaging. Phys Med Biol 62, 2315.Google Scholar
Burvall, A, Lundström, U, Takman, PA, Larsson, DH & Hertz, HM (2011). Phase retrieval in X-ray phase-contrast imaging suitable for tomography. Opt Express 19, 10359–10376.Google Scholar
Chen, RC, Xie, HL, Rigon, L, Longo, R, Castelli, E & Xiao, TQ (2011). Phase retrieval in quantitative x-ray microtomography with a single sample-to-detector distance. Opt Lett 36, 1719–1721.Google Scholar
Chou, CY & Anastasio, MA (2009). Influence of imaging geometry on noise texture in quantitative in-line X-ray phase-contrast imaging. Opt Express 17, 14466–14480.Google Scholar
Donnelly, EF, Lewis, KG, Wolske, KM, Pickens, DR & Price, RR (2005). Characterization of the phase-contrast radiography edge-enhancement effect in a cabinet x-ray system. Phys Med Biol 51, 21.Google Scholar
Donnelly, EF & Price, RR (2002). Quantification of the effect of kVp on edge-enhancement index in phase-contrast radiography. Med Phys 29, 999–1002.Google Scholar
Donnelly, EF, Price, RR & Pickens, DR (2003). Quantification of the effect of system and object parameters on edge enhancement in phase-contrast radiography. Med Phys 30, 2888–2896.Google Scholar
EXTREMA (2015). Extrema 2015—challenges in X-ray tomography. Available at http://www.esrf.eu/home/events/conferences/2015/extrema-2015---challenges-in-x-ray-tomography.html (accessed March 12, 2019).Google Scholar
Gureyev, TE, Mayo, SC, Myers, DE, Nesterets, Y, Paganin, DM, Pogany, A, Stevenson, AW & Wilkins, SW (2009). Refracting Röntgen's rays: Propagation-based x-ray phase contrast for biomedical imaging. J Appl Phys 105, 102005.Google Scholar
Gureyev, TE, Nesterets, YI, de Hoog, F, Schmalz, G, Mayo, SC, Mohammadi, S & Tromba, G (2014). Duality between noise and spatial resolution in linear systems. Opt Express 22, 9087–9094.Google Scholar
Gureyev, TE, Nesterets, YI, Stevenson, AW, Miller, PR, Pogany, A & Wilkins, SW (2008). Some simple rules for contrast, signal-to-noise and resolution in in-line x-ray phase-contrast imaging. Opt Express 16, 3223–3241.Google Scholar
Gureyev, TE, Paganin, DM, Myers, GR, Nesterets, YI & Wilkins, SW (2006). Phase-and-amplitude computer tomography. Appl Phys Lett 89, 034102.Google Scholar
Häggmark, I, Vågberg, W, Hertz, HM & Burvall, A (2017). Comparison of quantitative multi-material phase-retrieval algorithms in propagation-based phase-contrast X-ray tomography. Opt Express 25, 33543–33558.Google Scholar
Langer, M, Cloetens, P, Guigay, JP & Peyrin, F (2008). Quantitative comparison of direct phase retrieval algorithms in in-line phase tomography. Med Phys 35, 4556–4566.Google Scholar
Matsuo, S, Katafuchi, T, Tohyama, K, Morishita, J, Yamada, K & Fujita, H (2005). Evaluation of edge effect due to phase contrast imaging for mammography. Med Phys 32, 2690–2697.Google Scholar
Morgan, KS, Paganin, DM & Siu, KK (2011). Quantitative single-exposure x-ray phase contrast imaging using a single attenuation grid. Opt Express 19, 19781–19789.Google Scholar
Nesterets, YI, Gureyev, TE & Dimmock, MR (2018). Optimisation of a propagation-based x-ray phase-contrast micro-CT system. J Phys D: Appl Phys 51, 115402.Google Scholar
Nesterets, YI, Wilkins, SW, Gureyev, TE, Pogany, A & Stevenson, AW (2005). On the optimization of experimental parameters for x-ray in-line phase-contrast imaging. Rev Sci Instrum 76, 093706.Google Scholar
Olivo, A, Diemoz, PC & Bravin, A (2012). Amplification of the phase contrast signal at very high x-ray energies. Opt Lett 37, 915–917.Google Scholar
Paganin, D, Barty, A, McMahon, PJ & Nugent, KA (2004). Quantitative phase-amplitude microscopy. III. The effects of noise. J Microsc 214, 51–61.Google Scholar
Paganin, D, Mayo, SC, Gureyev, TE, Miller, PR & Wilkins, SW (2002). Simultaneous phase and amplitude extraction from a single defocused image of a homogeneous object. J Microsc 206, 33–40.Google Scholar
Pogany, A, Gao, D & Wilkins, SW (1997). Contrast and resolution in imaging with a microfocus x-ray source. Rev Sci Instrum 68, 2774–2782.Google Scholar
Wilkins, SW, Gureyev, TE, Gao, D, Pogany, A & Stevenson, AW (1996). Phase-contrast imaging using polychromatic hard X-rays. Nature 384, 335.Google Scholar
Wu, X & Liu, H (2003). Clinical implementation of x-ray phase-contrast imaging: Theoretical foundations and design considerations. Med Phys 30, 2169–2179.Google Scholar
Wu, X, Liu, H & Yan, A (2005). Optimization of X-ray phase-contrast imaging based on in-line holography. Nucl Instrum Meth Phys Res B 234, 563–572.Google Scholar
Zhou, Z, Zhang, L, Guo, B, Ma, W, Zhang, L, Li, J, Zhao, H, Jiang, J & Gao, F (2018). Improved phase-attenuation duality method with space-frequency joint domain iterative regularization. Med Phys 45, 3681–3696.Google Scholar