Nuclear Techniques ›› 2015, Vol. 38 ›› Issue (9): 90101-090101.doi: 10.11889/j.0253-3219.2015.hjs.38.090101


Noise analysis of cosine fitting radiography for diffraction enhanced imaging

BAO Yuan1,2 WANG Yan2 ZHU Peiping1,2 WU Ziyu1,2   

  1. 1(National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029, China) 2(Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China)
  • Received:2014-08-28 Revised:2015-03-10 Online:2015-09-10 Published:2015-09-10
  • Supported by:

    the States Key Project for Fundamental Research;the Science Fund for Creative Research Groups

Abstract: Background: Diffraction enhanced imaging (DEI) is a powerful phase contrast imaging technique. Purpose: This study aims to investigate the noise properties of a new simple cosine fitting radiography for DEI based on the angular signal response imaging prototype. Methods: The rocking curve can be treated as a angular signal response and a simple multi-information retrieval algorithm based on the cosine function fitting. A comprehensive analysis of noise properties in DEI, based on a noise model including the fluctuation of the photon source, and a bias of the analyzer crystal are also given. The validations have been performed with Monte Carlo simulations based on the Geant4 toolkit combined with the refractive process of X-ray and synchrotron radiation experimental data. Results: The cosine fitting radiography (CFR) has been verified by Monte Carlo simulations and experimental data which are in good agreement with each other. The noise penalty is drastically reduced with high photon flux, high visibility and high angular precision. Conclusions: Based on the angular signal response function prototype, we analyze and calculate the noise properties of DEI. In addition, the analytical method can build a strong connection between DEI and grating-based phase contrast imaging (GDPCI) and widely suitable for all kinds of measurement noises in angular signal response imaging prototype. The analysis is useful to understand the noise characteristics of DEI images and improve the signal-noise-ratio of the extracted information for biomedical imaging and material science.

Key words: Diffraction enhanced imaging, Noise analysis, Cosine fitting radiography, Monte Carlo simulations