Presentation + Paper
3 June 2022 Iterative reconstruction of the electron density and effective atomic number using a non-linear forward model
K. Aditya Mohan, Kyle M. Champley, Albert W. Reed, Steven M. Glenn, Harry E. Martz Jr.
Author Affiliations +
Abstract
For material identification, characterization, and quantification, it is useful to estimate system-independent material properties that do not depend on the detailed specifications of the X-ray computed tomography (CT) system such as spectral response. System independent ρe and Ze (SIRZ) refers to a suite of methods for estimating the system independent material properties of electron density (ρe) and effective atomic number (Ze) of an object scanned using dual-energy X-ray CT (DECT). The current state-of-the-art approach, SIRZ-2, makes certain approximations that lead to inaccurate estimates for large atomic numbered (Ze) materials. In this paper, we present an extension, SIRZ-3, which iteratively reconstructs the unknown ρe and Ze while avoiding the limiting approximations made by SIRZ-2. Unlike SIRZ-2, this allows SIRZ-3 to accurately reconstruct ρe and Ze even at large Ze. SIRZ-3 relies on the use of a new non-linear differentiable forward measurement model that expresses the DECT measurement data as a direct analytical function of ρe and Ze. Leveraging this new forward model, we use an iterative optimization algorithm to reconstruct (or solve for) ρe and Ze directly from the DECT data. Compared to SIRZ-2, we show that the magnitude of performance improvement using SIRZ-3 increases with increasing values for Ze.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
K. Aditya Mohan, Kyle M. Champley, Albert W. Reed, Steven M. Glenn, and Harry E. Martz Jr. "Iterative reconstruction of the electron density and effective atomic number using a non-linear forward model", Proc. SPIE 12104, Anomaly Detection and Imaging with X-Rays (ADIX) VII, 1210403 (3 June 2022); https://doi.org/10.1117/12.2625136
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KEYWORDS
Signal attenuation

X-rays

Data modeling

Mathematical modeling

CT reconstruction

Dual energy imaging

Optimization (mathematics)

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