CT理论与应用研究2026，Vol.35Issue(4)：724-734,11.DOI:10.15953/j.ctta.2025.356
面向稀疏角CT重建的投影先验引导均值回归扩散桥模型
Mean-Reverting Diffusion Bridge with Projection Prior for Sparse CT Reconstruction
摘要
Abstract
In sparse-view computed tomography(CT),incomplete projection data often lead to artifacts,edge blurring,and structural distortions in the reconstructed images.To address this challenge,this study proposes a diffusion bridge model based on the Ornstein-Uhlenbeck(OU)process for the conditional completion of missing projection-domain data to enable high-quality sparse-view reconstruction.The proposed method leverages the mean-reverting property of the OU process to establish a physically consistent stochastic diffusion mechanism.The diffusion bridge constraint anchors the sampling trajectory between the reconstruction prior and sparse projections,thereby achieving high-fidelity restoration of the missing data.Furthermore,a multiscale feature fusion module in the wavelet domain is incorporated into the network architecture to effectively integrate low-frequency structural information with high-frequency texture details,thereby enhancing the capability of the model to recover fine image features.Experimental results demonstrate that under the same sparse-view conditions,the proposed method outperforms existing state-of-the-art approaches in terms of both visual quality and quantitative metrics,confirming its effectiveness for sparse-view CT reconstruction tasks.关键词
计算机断层成像/扩散桥模型/正弦图先验/离散小波变换Key words
computed tomography/diffusion bridge model/sinogram prior/discrete wavelet transform分类
数理科学引用本文复制引用
李颜,施柳,刘且根..面向稀疏角CT重建的投影先验引导均值回归扩散桥模型[J].CT理论与应用研究,2026,35(4):724-734,11.基金项目
国家优秀青年科学基金(先验信息表示与医学成像重建(62122033)). （先验信息表示与医学成像重建(62122033）
