Classification of OME with Eardrum Otoendoscopic Images Using Hybrid-Based Deep Models, NCA, and Gaussian Method

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dc.contributor.authorBingol, Harun
dc.date.accessioned2026-06-19T06:38:06Z
dc.date.available2026-06-19T06:38:06Z
dc.date.issued2022
dc.departmentMalatya Turgut Özal Üniversitesi
dc.description.abstractOtitis media with effusion (OME) is defined as a middle ear disease that occurs with the accumulation of fluid in the posterior part of the eardrum, usually without any symptoms. When OME disease is not treated, some negative consequences arise that deeply affect the education, social and cultural life of the patient. OME disease is a difficult issue to diagnose by specialists. In this article, autoendoscopic images of the eardrum have been classified using deep learning methods to help specialists in the diagnosis of OME. In this study, a hybrid deep model based on artificial intelligence is proposed. In the proposed hybrid model, feature maps were obtained using Efficientnetb0 and Densenet201 architectures from both the original dataset and the improved dataset using the gaussian method. Then, the merging process was applied to these feature maps. Unnecessary features are eliminated by applying NCA dimension reduction to the combined feature map. The most valuable features obtained at the end of the optimization process are classified in different machine learning classifiers. The proposed model reached a very competitive accuracy value of 98.20% in the SVM classifier.
dc.identifier.doi10.18280/ts.390422
dc.identifier.endpage1302
dc.identifier.issn0765-0019
dc.identifier.issn1958-5608
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85140140133
dc.identifier.scopusqualityN/A
dc.identifier.startpage1295
dc.identifier.urihttps://doi.org/10.18280/ts.390422
dc.identifier.urihttps://hdl.handle.net/20.500.12899/5388
dc.identifier.volume39
dc.identifier.wosWOS:000867397500021
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorBingol, Harun
dc.language.isoen
dc.publisherInt Information & Engineering Technology Assoc
dc.relation.ispartofTraitement du Signal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20260612
dc.subjectCnn
dc.subjectGaussian Method
dc.subjectOtoendoscopic Images
dc.subjectNca
dc.subjectOtitis Media With Effusion
dc.titleClassification of OME with Eardrum Otoendoscopic Images Using Hybrid-Based Deep Models, NCA, and Gaussian Method
dc.typeArticle

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