ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2017
[Metal artifact reduction for dental implants in kilovoltage computed tomography using megavoltage cone-beam computer tomography].
Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Metal artifacts reduction in kV-CT images with polymetallic dentures and complex metals based on MV-CBCT images in radiotherapy.Scientific reports · 2023Article
- Cone-beam computed tomography artifacts in the presence of dental implants and associated factors: an integrative review.Imaging science in dentistry · 2021Article
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5 authors.
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Abstract
This paper proposes a novel metal artifact reduction (MAR) algorithm for dental implants in kilovoltage computed tomography (kVCT) using megavoltage cone-beam computer tomography (MVCBCT). Firstly, two CT images were derived by scanning patient with dental implants using kVCT and MVCBCT. Metal image was derived by thresholding segmentation in kVCT. MVCBCT and kVCT images were fused to generate prior image which was forward projected to get surrogate sinogram of metal trace. The corrected image was generated by filtered backprojection (FBP) reconstruction in corrected sinogram. The results of proposed algorithm were compared with other frequently-used metal artifact reduction algorithm, such as normalized MAR (NMAR), normalized MAR using MVCBCT prior images (NMAR-MV), and linear interpolation MAR (LIMAR). The normalized root mean square deviation (NRMSD) and mean absolute deviation (MAD) were computed. The experiment showed that the proposed method removed serious metal artifacts without introducing new artifacts. The values of NRMSD and MAD for proposed method were the minimum in all methods. The values of NRMSD for NMAR, NMAR-MV, LIMAR and the proposed method were 21.0%, 22.1%, 41.9% and 17.0% respectively. And MAD values of them were 232, 235, 553, 205 HU, respectively. In conclusion, the proposed metal artifact reduction algorithm can successfully suppress metal artifacts for dental implants, and greatly improve the quality of CT image.
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