Hybrid framework for feasible modeling of an edge illumination X-ray phase-contrast imaging system at a human scale.

Here, we present a hybrid approach for simulating an edge illumination X-ray phase-contrast imaging (EIXPCi) set-up using graphics processor units (GPU) with a high degree of accuracy. In this study, the applicability of pixel, mesh and non-uniform rational B-splines (NURBS) objects to carry out realistic maps of X-ray phase-contrast distribution at a human scale is accounted for by using numerical anthropomorphic phantoms and a very fast and robust simulation framework which integrates total interaction probabilities along selected X-ray paths. We exploit the mathematical and algorithmic properties of NURBS and describe how to represent human scale phantoms in an edge illumination X-ray phase-contrast model. The presented implementation allows the modeling of a variety of physical interactions of x-rays with different mathematically described objects and the recording of quantities, e.g. path integrals, interaction sites and deposited energies. Furthermore, our efficient, scalable and optimized hybrid Monte Carlo and ray-tracing projector can be used in iterative reconstruction algorithms on multi GPU heterogeneous systems. The preliminary results of our innovative approach show the fine performance of an edge illumination X-ray phase-contrast medical imaging system on various human-like soft tissues with noticeably reduced computation time. Our approach to the EIXPCi modeling confirms that building a true imaging system at a human scale should be possible and the simulations presented here aim at its future development.

Edge-illumination x-ray phase contrast imaging restoration using discrete curvelet regularization transform.

This article considers the problem of recovering edge-illumination x-ray phase contrast (EIXPC) images from a set of potentially Poisson noisy projection measurements. The authors cast a recovery as a sparse regularization problem based on Anscombe multiscale variance stabilizing transform (MS-VST) with fast discrete curvelet transform which was applied to simulated edge-illumination x-ray phase contrast images. For accurate modelling, the noise characteristics of the EIXPCi data are used to determine the relative importance of each projection. Two implementations of curvelet sparse regularization transforms were applied, including the unequally-spaced fast Fourier transform and the wrapping-based transform. The algorithms were evaluated in terms of contrast improvement, quality of image restoration, object perceptibility, and peak signal-to-noise ratio. The methods provide nearly optimal solution without excessive memory and recovery time requirement. The performance of the proposed algorithms is demonstrated through a series of complex numerical geometric and anthropomorphic phantom studies. The results of numerical simulations demonstrate that the discrete curvelet transform with MS-VST is fast and robust, and it can effectively improve image quality, preserve and enhance edges and restore lost information while significantly reducing the noise. Additionally, both sparse sampling and decreasing x-ray tube current (i.e. noisy data) lead to the reduction of radiation dose in the x-ray imaging.

Analytical reconstructions of intensity modulated x-ray phase-contrast imaging of human scale phantoms.

This paper presents analytical approach to modeling of a full planar and volumetric acquisition system with image reconstructions originated from partial illumination x-ray phase-contrast imaging at a human scale using graphics processor units. The model is based on x-ray tracing and wave optics methods to develop a numerical framework for predicting the performance of a preclinical phase-contrast imaging system of a human-scaled phantom. In this study, experimental images of simple numerical phantoms and high resolution anthropomorphic phantoms of head and thorax based on non-uniform rational b-spline shapes (NURBS) prove the correctness of the model. Presented results can be used to simulate the performance of partial illumination x-ray phase-contrast imaging system on various preclinical applications.

Transmission phase gratings fabricated with direct laser writing as color filters in the visible.

Simple diffraction structures having the form of a regular grid of pillars can generate a significant range of hues in white light transmission due to color-dependent diffraction into higher orders. We present the fabrication of such submicrometer scale structures by three dimensional laser two-photon photolithography, results of their optical properties measurements and compare the latter with numerical simulations.