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Abstract
Clinical studies performed using computer simulation are inexpensive, flexible methods that can be used to study aspects of a proposed imaging technique prior to a full clinical study. Typically, lesions are simulated into (experimental) data to assess the clinical potential of new methods or algorithms. In grating-based phase-contrast imaging (GB-PCI), full wave simulations are, however, computationally expensive due to the high periodicity of the gratings and therefore not practically applicable when large data sets are required. This work describes the development of a hybrid modelling platform that combines analytical and empirical input data for a more rapid simulation of GB-PCI images with little loss of accuracy. Instead of an explicit implementation of grating details, measured summary metrics (i.e. visibility, flux, noise power spectra, presampling modulation transfer function) are applied in order to generate transmission and differential phase images with large fields of view. Realistic transmission and differential phase images were obtained with good quantitative accuracy. The different steps of the simulation framework, as well as the methods to measure the summary metrics, are discussed in detail such that the technique can be easily customized for a given system. The platform offers a fast, accurate alternative to full wave simulations when the focus switches from grating/system design and set up to the generation of GB-PCI images for an established system.
Highlights
Phase-sensitive x-ray imaging has, in recent years, evolved into a promising addition to conventional x-ray imaging
Comparison of the object-disturbed pattern with the original pattern enables the construction of transmission (Tr), differential phase and dark field (DF) images (David et al 2002, Momose et al 2003, Pfeiffer et al 2006)
Analytical object model For a simple object like the PMMA sphere, close agreement between simulation and experiment is found as demonstrated in figure 2
Summary
Phase-sensitive x-ray imaging has, in recent years, evolved into a promising addition to conventional x-ray imaging. Grating-based phase-contrast imaging (GB-PCI) yields, via a stepping sequence, a familiar attenuation or transmission (Tr) image and two additional images: a differential phase (dP) and a dark field (DF) image The former visualizes the refraction effects caused by phase shifts induced by the object, while the latter is related to subpixel structure within the object. Others use computationally expensive Monte Carlo methods, where refraction is included via ray tracing (Wang et al 2009) or where diffraction effects based on the Huygens-Fresnel principle are included (Cipiccia et al 2014) While these methods offer an accurate and detailed simulation of signal transfer, the complexity of these frameworks make them computationally expensive with limited applicability for simulation of simulation studies of clinical tasks
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