Projection Decomposition for Dual-energy Computed Tomography

TL;DR

This paper introduces a novel projection decomposition method for dual-energy CT that combines analytical and optimization techniques to accurately quantify material components, improving image reconstruction quality.

Contribution

It proposes a new combined analytical and optimization approach for dual-energy CT projection decomposition, enhancing material quantification accuracy.

Findings

Outperforms classical methods in numerical tests

Accurately quantifies photoelectric and Compton components

Improves dual-energy CT image reconstruction quality

Abstract

Dual-energy computed tomography (CT) is to reconstruct images of an object from two projection datasets generated from two distinct x-ray source energy spectra. It can provide more accurate attenuation quantification than conventional CT with a single x-ray energy spectrum. In the diagnostic energy range, x-ray energy-dependent attenuation can be approximated as a linear combination of photoelectric absorption and Compton scattering. Hence, two physical components of x-ray attenuation can be determined from two spectral informative projection datasets to achieve monochromatic imaging and material decomposition. In this paper, a projection decomposition method is proposed for the image reconstruction in dual-energy CT. This method combines both an analytical algorithm and a single-variable optimization method to solve the non-linear polychromatic x-ray integral model, allowing accurate quantification of photoelectric absorption and Compton scattering components. Numerical tests are performed to illustrate the merit of the proposed method by comparing with classical projection decomposition methods.