工件(错误)
计算机科学
探测器
计算机视觉
投影(关系代数)
人工智能
迭代重建
算法
迭代法
领域(数学分析)
断层摄影术
戒指(化学)
锥束ct
图像(数学)
最优化问题
缩小
重建算法
模式识别(心理学)
图像处理
合成数据
图像分割
优化算法
锥束ct
对偶(语法数字)
对比度(视觉)
作者
Yanwei Qin,Xiaohui Su,Xin Lu,Baodi Yu,Yunsong Zhao,Fanyong Meng
标识
DOI:10.1109/tip.2026.3652008
摘要
Compared to traditional computed tomography (CT), photon-counting detector (PCD)-based CT provides significant advantages, including enhanced CT image contrast and reduced radiation dose. However, owing to the current immaturity of PCD technology, scanned PCD data often contain stripe artifacts resulting from non-functional or defective detector units, which subsequently introduce ring artifacts in reconstructed CT images. The presence of ring artifact may compromise the accuracy of CT values and even introduce pseudo-structures, thereby reducing the application value of CT images. In this paper, we propose a dual-domain optimization model that takes advantage of the distribution characteristics of the stripe artifact in 3D projection data and the prior features of reconstructed 3D CT images. Specifically, we demonstrate that stripe artifact in 3D projection data exhibit both group sparsity and low-rank properties. Building on this observation, we propose a TLT (TV- $l_{2,1}$ -Tucker) model to eliminate ring artifact in PCD-based cone beam CT (CBCT). In addition, an efficient iterative algorithm is designed to solve the proposed model. The effectiveness of both the model and the algorithm is evaluated through simulated and real data experiments. Experimental results demonstrate that the proposed method outperforms existing state-of-the-art approaches.
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