Metal artifacts reduction in kV-CT images with polymetallic dentures and complex metals based on MV-CBCT images in radiotherapy

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作者
Xiaochen Ni
Zhonghua Shi
Xinmao Song
Tianci Tang
Shengwei Li
Zhenfeng Hou
Wei Zhang
Wei Fang Wang
Fu Chen
Ji Li
Gang Yang
Ruichen Li
Xiaoshen Wang
机构
[1] Fudan University,Department of Radiotherapy, Eye & ENT Hospital
[2] Shanghai United Imaging Healthcare Co.,undefined
[3] Ltd,undefined
[4] Fudan University,undefined
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Scientific Reports | / 13卷
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摘要
This paper proposes a metal artifact reduction method of using MV-CBCT images to correct metal artifacts in kV-CT images, especially for the complex metal artifacts caused by multi-metal interaction of patients with head and neck tumors. The different tissue regions are segmented in the MV-CBCT images to obtain template images and the metal region is segmented in the kV-CT images. Forward projection is performed to get sinogram of the template images, kV-CT images and metal region images. Artifact images can be reconstructed through those sonograms. Corrected images is generated by subtracting the artifact images from the original kV-CT images. After the first correction, the template images are generated again and brought into the previous step for iteration to get better correction result. CT data set of 7 patients are used in this study, compared with linear interpolation metal artifact (LIMAR) and normalized metal artifact reduction method, mean relative error of CT value is reduced by 50.5% and 63.3%, noise is reduced by 56.2% and 58.9%. The Identifiability Score of the tooth, upper/lower jaw, tongue, lips, masseter muscle and cavity in the corrected images by the proposed method have significantly improved (P < 0.05) than original images. The artifacts correction method proposed in this paper can effectively remove the metal artifacts in the images and greatly improve the CT value accuracy, especially in the case of multi-metal and complex metal implantation.
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