Zeng Gengsheng L
Department of Computer Science, Utah Valley University, Orem, UT, 84058, USA.
Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA.
Vis Comput Ind Biomed Art. 2022 Jan 2;5(1):1. doi: 10.1186/s42492-021-00094-w.
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.
X射线计算机断层扫描中的金属物体可能会导致严重的伪影。目前最先进的金属伪影减少方法属于正弦图修复类别，并且是迭代方法。本文提出了一种投影域算法来减少金属伪影。在该算法中，未知量是受金属影响的投影，而目标函数是在图像域中建立的。目标函数中未使用数据保真项。所提出算法的目标函数由两项组成：去除金属后的图像的总变差和图像中负像素的能量。在修改受金属影响的投影后，通过滤波反投影算法重建最终图像。所提出算法的可行性已通过实际实验数据得到验证。
