A novel crystal-analyzer phase retrieval algorithm and its noise property

2015 ◽  
Vol 22 (3) ◽  
pp. 786-795 ◽  
Author(s):  
Yuan Bao ◽  
Yan Wang ◽  
Panyun Li ◽  
Zhao Wu ◽  
Qigang Shao ◽  
...  
Keyword(s):  
Phase Retrieval ◽  
Signal To Noise Ratio ◽  
Transfer Characteristic ◽  
Photon Flux ◽  
Retrieval Algorithm ◽  
X Rays ◽  
Contrast Imaging ◽  
Signal To Noise ◽  
Noise Characteristics ◽  
Signal Response

A description of the rocking curve in diffraction enhanced imaging (DEI) is presented in terms of the angular signal response function and a simple multi-information retrieval algorithm based on the cosine function fitting. A comprehensive analysis of noise properties of DEI is also given considering the noise transfer characteristic of the X-ray source. The validation has been performed with synchrotron radiation experimental data and Monte Carlo simulations based on theGeant4toolkit combined with the refractive process of X-rays, which show good agreement with each other. Moreover, results indicate that the signal-to-noise ratios of the refraction and scattering images are about one order of magnitude better than that of the absorption image at the edges of low-Zsamples. The noise penalty is drastically reduced with the increasing photon flux and visibility. Finally, this work demonstrates that the analytical method can build an interesting connection between DEI and GDPCI (grating-based differential phase contrast imaging) and is widely suitable for a variety of measurement noise in the angular signal response imaging prototype. The analysis significantly contributes to the understanding of noise characteristics of DEI images and may allow improvements to the signal-to-noise ratio in biomedical and material science imaging.

Improved Signal-to-Noise Ratio in Laboratory-Based Phase Contrast Tomography

2012 ◽  
Vol 18 (2) ◽  
pp. 399-405 ◽  
Author(s):  
Matthieu N. Boone ◽  
Yoni De Witte ◽  
Manuel Dierick ◽  
Ana Almeida ◽  
Luc Van Hoorebeke
Keyword(s):  
Phase Contrast ◽  
Phase Retrieval ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
X Rays ◽  
Signal To Noise ◽  
Retrieval Algorithms ◽  
Significant Phenomenon ◽  
Noise Ratio ◽  
3D Volume

AbstractIn conventional X-ray microtomography (μCT), the three-dimensional (3D) distribution of the attenuation coefficient of X-rays is measured and reconstructed in a 3D volume. As spatial resolution increases, the refraction of X-rays becomes a significant phenomenon in the imaging process. Although this so-called phase contrast was initially a cumbersome feature in lab-based μCT, special phase retrieval algorithms were developed to exploit these effects. Clear advantages in terms of visualization and analysis can be seen when phase retrieval algorithms are applied, including an increased signal-to-noise ratio. In this work, this is demonstrated both on simulated and measured data.

Stochastic optimal phase retrieval algorithm for high-contrast imaging

2003 ◽  
Author(s):  
Amir Give'on ◽  
N. Jeremy Kasdin ◽  
Robert J. Vanderbei ◽  
David N. Spergel ◽  
Michael G. Littman ◽  
...  
Keyword(s):  
Phase Retrieval ◽  
Retrieval Algorithm ◽  
High Contrast ◽  
Contrast Imaging ◽  
High Contrast Imaging ◽  
Phase Retrieval Algorithm

Near-field x-ray phase contrast imaging and phase retrieval algorithm

2005 ◽  
Vol 14 (4) ◽  
pp. 796-801 ◽  
Author(s):  
Zhu Hua-Feng ◽  
Xie Hong-Lan ◽  
Gao Hong-Yi ◽  
Chen Jian-Wen ◽  
Li Ru-Xin ◽  
...  
Keyword(s):  
Phase Contrast ◽  
Phase Retrieval ◽  
Near Field ◽  
Phase Contrast Imaging ◽  
Retrieval Algorithm ◽  
Contrast Imaging ◽  
X Ray ◽  
Phase Retrieval Algorithm

A phase retrieval algorithm for polychromatic x-ray in-line phase contrast imaging

2012 ◽  
Author(s):  
Xue-jun Guo ◽  
Xiao-lin Liu ◽  
Mu Gu ◽  
Chen Ni ◽  
Bo Liu ◽  
...  
Keyword(s):  
Phase Contrast ◽  
Phase Retrieval ◽  
Phase Contrast Imaging ◽  
Retrieval Algorithm ◽  
Contrast Imaging ◽  
X Ray ◽  
Phase Retrieval Algorithm

scholarly journals Sensitivity of edge illumination X-ray phase-contrast imaging

2014 ◽  
Vol 372 (2010) ◽  
pp. 20130128 ◽  
Author(s):  
P. C. Diemoz ◽  
M. Endrizzi ◽  
A. Bravin ◽  
I. K. Robinson ◽  
A. Olivo
Keyword(s):  
Theoretical Model ◽  
Phase Contrast ◽  
Angular Resolution ◽  
Signal To Noise Ratio ◽  
Phase Contrast Imaging ◽  
High Angular Resolution ◽  
Contrast Imaging ◽  
Signal To Noise ◽  
X Ray ◽  
Set Up

Recently, we developed a theoretical model that can predict the signal-to-noise ratio for edge-like features in phase-contrast images. This model was then applied for the estimation of the sensitivity of three different X-ray phase-contrast techniques: propagation-based imaging, analyser-based imaging and grating interferometry. We show here how the same formalism can be used also in the case of the edge illumination (EI) technique, providing results that are consistent with those of a recently developed method for the estimation of noise in the retrieved refraction image. The new model is then applied to calculate, in the case of a given synchrotron radiation set-up, the optimum positions of the pre-sample aperture and detector edge to maximize the sensitivity. Finally, an example of the extremely high angular resolution achievable with the EI technique is presented.

Efficient implementation of X-ray ghost imaging based on a modified compressive sensing algorithm

2022 ◽  
Author(s):  
Haipeng Zhang ◽  
Ke Li ◽  
Changzhe Zhao ◽  
Jie Tang ◽  
Tiqiao Xiao
Keyword(s):  
Image Reconstruction ◽  
Compressive Sensing ◽  
Signal To Noise Ratio ◽  
Efficient Implementation ◽  
X Rays ◽  
Ghost Imaging ◽  
Signal To Noise ◽  
X Ray ◽  
Efficient Data ◽  
Reconstruction Time

Abstract Towards efficient implementation of X-ray ghost imaging (XGI), efficient data acquisition and fast image reconstruction together with high image quality are preferred. In view of radiation dose resulted from the incident X-rays, fewer measurements with sufficient signal-to-noise ratio (SNR) are always anticipated. Available methods based on linear and compressive sensing algorithms cannot meet all the requirements simultaneously. In this paper, a method based a modified compressive sensing algorithm called CGDGI, is developed to solve the problem encountered in available XGI methods. Simulation and experiments demonstrated the practicability of CGDGI-based method for the efficient implementation of XGI. The image reconstruction time of sub-second implicates that the proposed method has the potential for real time XGI.

scholarly journals Quantitative X-ray phase contrast waveguide imaging of bacterial endospores

2015 ◽  
Vol 48 (2) ◽  
pp. 464-476 ◽  
Author(s):  
R. N. Wilke ◽  
M. Hoppert ◽  
M. Krenkel ◽  
M. Bartels ◽  
T. Salditt
Keyword(s):  
Phase Contrast ◽  
Phase Retrieval ◽  
Mass Density ◽  
Field Of View ◽  
Large Field ◽  
Single Individual ◽  
X Rays ◽  
Contrast Imaging ◽  
X Ray ◽  
Freeze Dried

Quantitative waveguide-based X-ray phase contrast imaging has been carried out on the level of single, unstained, unsliced and freeze-dried bacterial cells ofBacillus thuringiensisandBacillus subtilisusing hard X-rays of 7.9 keV photon energy. The cells have been prepared in the metabolically dormant state of an endospore. The quantitative phase maps obtained by iterative phase retrieval using a modified hybrid input–output algorithm allow for mass and mass density determinations on the level of single individual endospores but include also large field of view investigations. Additionally, a direct reconstruction based on the contrast transfer function is investigated, and the two approaches are compared. Depending on the field of view and method, a resolution down to 65 nm was achieved at a maximum applied dose of below 5 × 105 Gy. Masses in the range of about ∼110–190 (20) fg for isolated endospores have been obtained.

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