Phase contrast imaging simulation and measurements using polychromatic sources with small source-object distances

Abstract

Phase contrast imaging is a technique widely used in synchrotron facilities for nondestructive analysis. Such technique can also be implemented through microfocus x-ray tube systems. Recently, a relatively new type of compact, quasimonochromatic x-ray sources based on Compton backscattering has been proposed for phase contrast imaging applications. In order to plan a phase contrast imaging system setup, to evaluate the system performance and to choose the experimental parameters that optimize the image quality, it is important to have reliable software for phase contrast imaging simulation. Several software tools have been developed and tested against experimental measurements at synchrotron facilities devoted to phase contrast imaging. However, many approximations that are valid in such conditions ͑e.g., large source-object distance, small transverse size of the object, plane wave approximation, monochromatic beam, and Gaussian-shaped source focal spot͒ are not generally suitable for x-ray tubes and other compact systems. In this work we describe a general method for the simulation of phase contrast imaging using polychromatic sources based on a spherical wave description of the beam and on a double-Gaussian model of the source focal spot, we discuss the validity of some possible approximations, and we test the simulations against experimental measurements using a microfocus x-ray tube on three types of polymers ͑nylon, poly-ethylene-terephthalate, and poly-methyl-methacrylate͒ at varying source-object distance. It will be shown that, as long as all experimental conditions are described accurately in the simulations, the described method yields results that are in good agreement with experimental measurements.

Monte Carlo simulation of X-ray imaging and spectroscopy experiments using quadric geometry and variance reduction techniques

“…Current work is focussed on the implementation of the response of realistic detectors for imaging (e.g., CMOS detectors) and for spectroscopy (e.g., Silicon Drift detectors) as devices that can be used within the program. New modules will soon be included in the program for a voxel-based description of sample geometry and for phase contrast imaging simulations [19]. XRMC is released under the GNU general public license and can be downloaded freely from http://github.com/golosio/xrmc.…”

“…In this work, we present a program for the simulation of X-ray imaging and spectroscopy experiments based on the Monte Carlo method by exploiting variance reduction techniques, with a description of the sample geometry based on quadric surfaces. Past versions of this program have been used in medical imaging [9][10][11][12][13], archaeometry [14][15][16] and beam characterisation [17][18][19] with X-ray tubes as well as with less conventional X-ray sources (e.g., inverse Compton scattering sources [9- 13,17,18]) for planning experimental setups, optimising experimental parameters and comparing theoretical models with experimental results. The code is written entirely in the C++ programming language.…”

Grating‐based x‐ray differential phase contrast imaging with twin peaks in phase‐stepping curves—phase retrieval and dewrapping

“…I(x,y,z 2 ) denotes the intensity immediately in front of grating G 2 , which can be expressed as the convolution between the intensity generated by a point source, i.e., with infinitesimal focal spot, and the geometrical projection of the source distribution I source (x, y) with finite focal spot through the object on the detector, 15,16 F. 3.…”

“…is a projection function representing the analyzer grating G 2 , l d the detector cell dimension, and I(x, y,z 2 ) the intensity immediately in front of G 2 , which can be expressed as 15,16 I…”

X-ray phase-contrast imaging with an Inverse Compton Scattering source

“…The fitting procedure for the flat-field is required due the shot-to-shot fluctuations of the beam (intensity, position and shape). A simulation [7] is compared to the normalized intensity profile (fig. 4).…”