Dual-Energy X-Ray Dark-Field Material Decomposition

• Published in: IEEE transactions on medical imaging 2021-03, Vol.40 (3), p.974-985
• Main Authors: Sellerer, Thorsten, Mechlem, Korbinian, Tang, Ruizhi, Taphorn, Kirsten Alexandra, Pfeiffer, Franz, Herzen, Julia
• Format: Article
• Language: English
• Subjects: Algorithms; Attenuation; Clinical diagnosis; Decomposition; Diagnosis; Energy; Imaging; Imaging modalities; Imaging techniques; lung; Medical diagnosis; Microstructure; quantification and estimation; Scattering; Spatial discrimination; Spatial resolution; X ray imagery; X ray spectra; X-ray imaging; X-ray imaging and computed tomography
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2020.3043303

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.