Joint-decoupled iterative CBCT reconstruction with hybrid scatter estimation and voxel-adaptive beam hardening correction

Cone-beam computed tomography (CBCT) is fundamentally challenged by scatter and beam hardening artifacts, which originate from X-ray scattering and the polychromatic nature of the X-ray spectrum, respectively. These two types of artifacts are intricately coupled in reconstructed images and manifest with similar streaking and cupping features, severely compromising high-precision CBCT imaging. This paper proposes a physics-driven iterative framework rooted in the polychromatic Polyquant attenuation model, which decouples these artifacts by establishing an optimization loop between scatter estimation and relative electron density (RED) reconstruction. We develop a hybrid strategy for scatter estimation, in which the first-order scattering component is analytically derived based on a polychromatic physical model to preserve high-frequency structural information, whereas the smoother multiple scattering component is efficiently estimated via an object-adaptive convolution module. Subsequently, for beam-hardening correction, we introduce a voxel-adaptive update mechanism that solves linearized, scatter-corrected polychromatic equations to derive optimal weights, enabling direct RED refinement without manual parameter tuning. The proposed method was validated through comprehensive studies on biomedical phantoms, utilizing both Monte Carlo simulations and physical experiments. Representative results demonstrate that the proposed method outperforms state-of-the-art techniques, with the mean relative error decreased from 11.96\% to 1.27\% for the anthropomorphic head phantom and from 12.55\% to 5.46\% for the physical Yin-Yang phantom.