Novel approaches to determine age and gender from dental x-ray images by using multiplayer perceptron neural networks and image processing techniques

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dc.authoridBasciftci, Fatih -- 0000-0003-1679-7416; AVUCLU, Emre -- 0000-0002-1622-9059
dc.contributor.authorAvuçlu, Emre
dc.contributor.authorBasçiftçi, Fatih
dc.date.accessioned13.07.201910:50:10
dc.date.accessioned2019-07-16T09:16:25Z
dc.date.available13.07.201910:50:10
dc.date.available2019-07-16T09:16:25Z
dc.date.issued2019
dc.departmentAksaray Teknik Bilimler Meslek Yüksekokulu
dc.description.abstractIt may be necessary to determine the identity or gender of a person for any reason (disasters, inheritance etc.). In such cases, forensic medical institutions are asked for help. Forensic science institutions try to estimate the age of people's teeth and bones. In this study, a novel algorithm was developed to keep these predictions at the highest level and to obtain definite results. The data base of 162 different tooth classes is created manually. All image sizes are 150x150 pixels. First, image preprocessing techniques have been applied to teeth images. These preprocessing techniques were first applied to teeth images. After this process, the segmentation process of the teeth images was performed to extract the feature by novel segmentation algorithm. Segmentation can be done automatically and dynamically. Numerical data obtained as a result of feature extraction from dental images is presented as an inputs to Multi layer perceptron neural network. In application, feature reduction can be performed. Thanks to the originally developed algorithm, the highest success rates were obtained with the highest 99.9% (full segment) and 100% (notfull segment) classification. After classification, for many dental groups the age estimate is performed with zero error. Application was developed as a multidisciplinary study. (C) 2019 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipSelcuk University Scientific Research Projects Coordinatorship/Konya, Turkey
dc.description.sponsorshipThis work is supported by the Selcuk University Scientific Research Projects Coordinatorship/Konya, Turkey.
dc.identifier.doi10.1016/j.chaos.2019.01.023
dc.identifier.endpage138en_US
dc.identifier.issn0960-0779
dc.identifier.issn1873-2887
dc.identifier.scopusqualityQ1
dc.identifier.startpage127en_US
dc.identifier.urihttps://doi.org/10.1016/j.chaos.2019.01.023
dc.identifier.urihttps://hdl.handle.net/20.500.12451/4592
dc.identifier.volume120en_US
dc.identifier.wosWOS:000459131600013
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elseiver Science Ltd.
dc.relation.ispartofChaos Solitons & Fractals
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAge Estimation
dc.subjectBackpropagation Algorithm
dc.subjectMultilayer Perceptron
dc.subjectPanoramic X-Ray
dc.subjectImage Processing Techniques
dc.titleNovel approaches to determine age and gender from dental x-ray images by using multiplayer perceptron neural networks and image processing techniques
dc.typeArticle

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