Detecting prosthetic restorations using artificial intelligence on panoramic radiographs

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dc.authorid0000-0002-6429-4197
dc.contributor.authorAltan, Bike
dc.contributor.authorGüneç, ?Hüseyin Gürkan
dc.contributor.authorÇınar, ?Şevki?
dc.contributor.authorKutal, Seçilay
dc.contributor.authorGülüm, Semih
dc.contributor.authorCesur Aydın, Kader
dc.date.accessioned2022-12-05T07:16:49Z
dc.date.available2022-12-05T07:16:49Z
dc.date.issued2022
dc.departmentİstanbul Medipol Üniversitesi, Diş Hekimliği Fakültesi, Ağız, Diş ve Çene Radyolojisi Ana Bilim Dalı
dc.description.abstractAim. This study applied a CNN (convolutional neural network) algorithm to detect prosthetic restorations on panoramic radiographs and to automatically detect these restorations using deep learning systems. Materials and Methods. This study collected a total of 5126 panoramic radiographs of adult patients. During model training, .bmp, .jpeg, and .png files for images and .txt files containing five different types of information are required for the labels. Herein, 10% of panoramic radiographs were used as a test dataset. Owing to labeling, 2988 crowns and 2969 bridges were formed in the dataset. Results. The mAP and mAR values were obtained when the confidence threshold was set at 0.1. TP, FP, FN, precision, recall, and F1 score values were obtained when the confidence threshold was 0.25. The YOLOv4 model demonstrated that accurate results could be obtained quickly. Bridge results were found to be more successful than crown results. Conclusion. The detection of prosthetic restorations with artificial intelligence on panoramic radiography, which is widely preferred in clinical applications, provides convenience to physicians in terms of diagnosis and time management.
dc.identifier.citationAltan, B., Güneç, ?H. G., Çınar, ?Ş., Kutal, S., Gülüm, S. ve Cesur Aydın, K. (2022). Detecting prosthetic restorations using artificial intelligence on panoramic radiographs. Scientific Programming, 2022. https://doi.org/10.1155/2022/6384905
dc.identifier.doi10.1155/2022/6384905
dc.identifier.issn1058-9244
dc.identifier.issn1875-919X
dc.identifier.scopus2-s2.0-85142445157
dc.identifier.scopusqualityQ3
dc.identifier.urihttps://doi.org/10.1155/2022/63849
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10071
dc.identifier.volume2022
dc.identifier.wos000888574200001en_US
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorCesur Aydın, Kader
dc.language.isoen
dc.publisherHindawi Limited
dc.relation.ispartofScientific Programmingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsAttribution 4.0 International*
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectPanoramic Radiographs
dc.subjectArtificial Intelligence
dc.subjectDetecting Prosthetic Restorations
dc.titleDetecting prosthetic restorations using artificial intelligence on panoramic radiographs
dc.typeArticle

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