A projection-domain iterative algorithm for metal artifact reduction by minimizing the total-variation norm and the negative-pixel energy.

4区 计算机科学 Q1 Arts and Humanities Visual Computing for Industry, Biomedicine, and Art Pub Date : 2022-01-02 DOI:10.1186/s42492-021-00094-w
Gengsheng L Zeng
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引用次数: 1

Abstract

Metal objects in X-ray computed tomography can cause severe artifacts. The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods. This paper proposes a projection-domain algorithm to reduce the metal artifacts. In this algorithm, the unknowns are the metal-affected projections, while the objective function is set up in the image domain. The data fidelity term is not utilized in the objective function. The objective function of the proposed algorithm consists of two terms: the total variation of the metal-removed image and the energy of the negative-valued pixels in the image. After the metal-affected projections are modified, the final image is reconstructed via the filtered backprojection algorithm. The feasibility of the proposed algorithm has been verified by real experimental data.

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基于总变分范数和负像元能量最小化的投影域迭代算法。
x射线计算机断层扫描中的金属物体会造成严重的伪影。目前最先进的金属伪影还原方法属于sinogram inpainting范畴,是一种迭代方法。本文提出了一种减少金属伪影的投影域算法。该算法以金属影响投影为未知量,在图像域建立目标函数。目标函数中没有使用数据保真度项。该算法的目标函数由两项组成:去金属图像的总变分和图像中负值像素的能量。在对金属影响的投影进行修改后,通过滤波后的反投影算法重建最终图像。实际实验数据验证了该算法的可行性。
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来源期刊
Visual Computing for Industry, Biomedicine, and Art
Visual Computing for Industry, Biomedicine, and Art Arts and Humanities-Visual Arts and Performing Arts
CiteScore
5.60
自引率
0.00%
发文量
28
审稿时长
5 weeks
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