Joint-decoupled iterative CBCT reconstruction with hybrid scatter estimation and voxel-adaptive beam hardening correction
Abstract
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.
Related
- Parameter-Decoupled Quantum Superresolution without Multiparameter Estimation
- Stable, Compact, and Direct Ghost-Cell Reconstruction: A Non-Iterative Approach for Embedded-Boundary Methods
- Optimal Resource Scaling for Early Fault Tolerant Iterative Quantum Phase Estimation under Cost Error Tradeoffs
- Toward Efficient End-to-End Quantum Elliptic PDE Solvers: a Multilevel Correction Algorithm for Direct Observable Estimation
- Particle-Number-Preserving Quantum Signal Processing for Thermal Properties: Canonical-Ensemble Estimation and Grand-Canonical Reconstruction
BibTeX
@misc{sun2026jointdecoupled,
title = {{Joint-decoupled iterative CBCT reconstruction with hybrid scatter estimation and voxel-adaptive beam hardening correction}},
author = {Jianing Sun and Jean Michel Létang and Qixiang Sun and Guangyin Li and Ligen Shi and Xing Zhao},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2607.15812},
eprint = {2607.15812},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2607.15812},
}
RIS
TY - UNPB
TI - Joint-decoupled iterative CBCT reconstruction with hybrid scatter estimation and voxel-adaptive beam hardening correction
AU - Jianing Sun
AU - Jean Michel Létang
AU - Qixiang Sun
AU - Guangyin Li
AU - Ligen Shi
AU - Xing Zhao
PY - 2026
DA - 2026/09/28
PB - arXiv
DO - 10.48550/arxiv.2607.15812
UR - https://arxiv.org/abs/2607.15812
AB - 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.
ER -