Energy-Coded Spectral CT Imaging Method Based on Projection Mix Separation

Abstract

Spectral CT can be used to perform material decomposition from polychromatic attenuation data, generate virtual monochromatic or virtual narrow-energy-width images in which beam hardening artifacts are suppressed, and provide detailed energy attenuation coefficients for material characterization. We propose an energy-coded spectral CT imaging method that is based on projection mix separation, which enables simultaneous energy decoding and image reconstruction. An X-ray energy-coded forward model is then constructed. Leveraging the Poisson statistical properties of the measurement data, we formulate a constrained optimization problem for both the energy-coded coefficient matrix and the material decomposition coefficient matrix, which is solved using a block coordinate descent algorithm. Simulations and experimental results demonstrate that the decoded energy spectrum distribution and virtual narrow-energy-width CT images are accurate and effective. The proposed method suppresses beam hardening artifacts and enhances the material identification capabilities of traditional CT.