A novel convolutional neural network-based approach for brain tumor classification using magnetic resonance images

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dc.contributor.authorÇınar, Necip
dc.contributor.authorKaya, Mehmet
dc.contributor.authorKaya, Buket
dc.contributor.orcid0000-0002-5106-6240
dc.contributor.orcid0000-0003-2995-8282
dc.contributor.orcid0000-0001-9505-181X
dc.date.accessioned2024-04-24T15:59:25Z
dc.date.available2024-04-24T15:59:25Z
dc.date.issued2023
dc.departmentDicle Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractBrain tumor is a disease that seriously threatens human health and can often be treated with risky surgeries. Experts detect brain tumor with high resolution magnetic resonance (MR) images. However, the expected accuracy value could not be reached in the studies carried out so far. The aim of this study is to develop a new approach for detecting brain tumor types using MR images. In the proposed approach, it is designed a CNN-based neural network from scratch. The results of the method were compared with existing networks. The proposed approach detected glioma tumors with 99.64%, meningiomas tumor with 96.53%, pituitary tumors with 98.39% and an average of 98.32% accuracy. The developed CNN based model is also compared with deep CNN models such as ResNet50, VGG19, DensetNet121 and InceptionV3, which are operated by transfer learning method. The results show that the proposed approach outperforms other deep neural networks.en_US
dc.identifier.citationÇınar, N., Kaya, M. ve Kaya, B. (2023). A novel convolutional neural network-based approach for brain tumor classification using magnetic resonance images. International Journal of Imaging Systems and Technology, 33(3), 895-908.
dc.identifier.doi10.1002/ima.22839
dc.identifier.endpage908en_US
dc.identifier.issn0899-9457
dc.identifier.issn1098-1098
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85144045791
dc.identifier.scopusqualityQ1
dc.identifier.startpage895en_US
dc.identifier.urihttps://doi.org/10.1002/ima.22839
dc.identifier.urihttps://hdl.handle.net/11468/14049
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/10.1002/ima.22839
dc.identifier.volume33en_US
dc.identifier.wosWOS:000895161700001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorÇınar, Necip
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofInternational Journal of Imaging Systems and Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial neural network modelsen_US
dc.subjectBrain tumor classificationen_US
dc.subjectConvolutional neural networken_US
dc.subjectDeep learningen_US
dc.titleA novel convolutional neural network-based approach for brain tumor classification using magnetic resonance imagesen_US
dc.titleA novel convolutional neural network-based approach for brain tumor classification using magnetic resonance images
dc.typeArticleen_US

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