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Evaluating the Precision of Automatic Segmentation of Teeth, Gingiva and Facial Landmarks for 2D Digital Smile Design Using Real-Time Instance Segmentation Network

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dc.contributor.author김종은-
dc.contributor.author김종은-
dc.contributor.author이슬기-
dc.date.accessioned2022-03-11T06:20:02Z-
dc.date.available2022-03-11T06:20:02Z-
dc.date.issued2022-02-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/188040-
dc.description.abstractDigital smile design (DSD) technology, which takes pictures of patients' faces together with anterior dentition and uses them for prosthesis design, has been recently introduced. However, the limitation of DSD is that it evaluates a patient with only one photograph taken in a still state, and the patient's profile cannot be observed from various viewpoints. Therefore, this study aims to segment the patient's anterior teeth, gingiva and facial landmarks using YOLACT++. We trained YOLACT++ on the annotated data of the teeth, lips and gingiva from the Flickr-Faces-HQ (FFHQ) data. We evaluated that the model trained by 2D candid facial images for the detection and segmentation of smile characteristics. The results show the possibility of an automated smile characteristic identification system for the automatic and accurate quantitative assessment of a patient's smile.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherMDPI AG-
dc.relation.isPartOfJOURNAL OF CLINICAL MEDICINE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleEvaluating the Precision of Automatic Segmentation of Teeth, Gingiva and Facial Landmarks for 2D Digital Smile Design Using Real-Time Instance Segmentation Network-
dc.typeArticle-
dc.contributor.collegeCollege of Dentistry (치과대학)-
dc.contributor.departmentDept. of Prosthodontics (보철과학교실)-
dc.contributor.googleauthorSeulgi Lee-
dc.contributor.googleauthorJong-Eun Kim-
dc.identifier.doi10.3390/jcm11030852-
dc.contributor.localIdA00927-
dc.contributor.localIdA00927-
dc.relation.journalcodeJ03556-
dc.identifier.eissn2077-0383-
dc.identifier.pmid35160303-
dc.subject.keyword2D candid facial image-
dc.subject.keywordYOLACT++-
dc.subject.keyworddeep learning-
dc.subject.keyworddetection-
dc.subject.keyworddigital dentistry-
dc.subject.keyworddigital smile design-
dc.subject.keywordsegmentation-
dc.contributor.alternativeNameKim, Jong Eun-
dc.contributor.affiliatedAuthor김종은-
dc.contributor.affiliatedAuthor김종은-
dc.citation.volume11-
dc.citation.number3-
dc.citation.startPage852-
dc.identifier.bibliographicCitationJOURNAL OF CLINICAL MEDICINE, Vol.11(3) : 852, 2022-02-
Appears in Collections:
2. College of Dentistry (치과대학) > Dept. of Prosthodontics (보철과학교실) > 1. Journal Papers

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