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Accuracy of digital model generated from CT data with metal artifact reduction algorithm

DC Field Value Language
dc.contributor.author이채나-
dc.contributor.author전국진-
dc.contributor.author최윤주-
dc.contributor.author한상선-
dc.date.accessioned2021-09-29T00:41:49Z-
dc.date.available2021-09-29T00:41:49Z-
dc.date.issued2021-05-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/183991-
dc.description.abstractThis study investigated whether metal artifact reduction (MAR) applied computed tomography (CT) scans could be used to generate precise digital models and explored possible correlations between the amount of metal artifact and model accuracy. Thirty maxillofacial CT scans were randomly selected and a MAR algorithm was applied. By subtracting the original and MAR-applied CT images, the amount of metal artifact was quantified. Digital models were generated from the original and the MAR-applied CT data. Paired digital models were superimposed and shape deviation in planar surface was measured at 10 points in 4 planes. Statistical analyses were performed to compare deviations and to assess correlations between the amount of artifact and deviation. The MAR algorithm reduced metal artifact in all cases. The overall mean deviation of the MAR-applied models was 0.0868 mm, with no significant difference according to the reference plane. The amount of artifact did not significantly influence the accuracy of the digital models. MAR-applied CT is a convenient source for digital modeling with clinically acceptable accuracy. The MAR algorithm can be used regardless of the amount of metal artifact, which are generated by dental prostheses, for the quick and convenient manipulation of dental digital models.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherNature Publishing Group-
dc.relation.isPartOfSCIENTIFIC REPORTS-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleAccuracy of digital model generated from CT data with metal artifact reduction algorithm-
dc.typeArticle-
dc.contributor.collegeCollege of Dentistry (치과대학)-
dc.contributor.departmentDept. of Oral and Maxillofacial Radiology (영상치의학교실)-
dc.contributor.googleauthorChena Lee-
dc.contributor.googleauthorAri Lee-
dc.contributor.googleauthorYoon Joo Choi-
dc.contributor.googleauthorKug Jin Jeon-
dc.contributor.googleauthorYoung Hyun Kim-
dc.contributor.googleauthorSang-Sun Han-
dc.identifier.doi10.1038/s41598-021-89298-x-
dc.contributor.localIdA05388-
dc.contributor.localIdA03503-
dc.contributor.localIdA05734-
dc.contributor.localIdA04283-
dc.relation.journalcodeJ02646-
dc.identifier.eissn2045-2322-
dc.identifier.pmid33990637-
dc.contributor.alternativeNameLee, Chena-
dc.contributor.affiliatedAuthor이채나-
dc.contributor.affiliatedAuthor전국진-
dc.contributor.affiliatedAuthor최윤주-
dc.contributor.affiliatedAuthor한상선-
dc.citation.volume11-
dc.citation.number1-
dc.citation.startPage10332-
dc.identifier.bibliographicCitationSCIENTIFIC REPORTS, Vol.11(1) : 10332, 2021-05-
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Oral and Maxillofacial Radiology (영상치의학교실) > 1. Journal Papers

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