Dual-energy X-ray dark-field material decomposition

TL;DR

This paper introduces a novel dual-energy X-ray dark-field imaging technique that enables material-specific microstructure decomposition, potentially enhancing clinical diagnosis by providing detailed information about microstructures below the spatial resolution.

Contribution

It develops a physical model and algorithms for dual-energy dark-field material decomposition, extending traditional attenuation-based methods to dark-field imaging.

Findings

Successful experimental demonstration of microstructure decomposition

Energy-dependent dark-field signals enable material differentiation

Potential for improved clinical microstructure analysis

Abstract

Dual-energy imaging is a clinically well-established technique that offers several advantages over conventional X-ray imaging. By performing measurements with two distinct X-ray spectra, differences in energy-dependent attenuation are exploited to obtain material-specific information. This information is used in various imaging applications to improve clinical diagnosis. In recent years, grating-based X-ray dark-field imaging has received increasing attention in the imaging community. The X-ray dark-field signal originates from ultra small-angle scattering within an object and thus provides information about the microstructure far below the spatial resolution of the imaging system. This property has led to a number of promising future imaging applications that are currently being investigated. However, different microstructures can hardly be distinguished with current X-ray dark-field imaging techniques, since the detected dark-field signal only represents the total amount of ultra small-angle scattering. To overcome these limitations, we present a novel concept called dual-energy X-ray dark-field material decomposition, which transfers the basic material decomposition approach from attenuation-based dual-energy imaging to the dark-field imaging modality. We develop a physical model and algorithms for dual-energy dark-field material decomposition and evaluate the proposed concept in experimental measurements. Our results suggest that by sampling the energy-dependent dark-field signal with two different X-ray spectra, a decomposition into two different microstructured materials is possible. Similar to dual-energy imaging, the additional microstructure-specific information could be useful for clinical diagnosis.