Deep Learning Based Melanoma Detection From Dermoscopic Images

dc.contributor.author Berkay M. en_US
dc.contributor.author Mergen E.H. en_US
dc.contributor.author Binici R.C. en_US
dc.contributor.author Bayhan Y. en_US
dc.contributor.author Gungor A. en_US
dc.contributor.author Okur E. en_US
dc.contributor.author Unay D. en_US
dc.contributor.author Türkan, Mehmet en_US
dc.date.accessioned 2023-06-16T15:00:42Z
dc.date.available 2023-06-16T15:00:42Z
dc.date.issued 2019 en_US
dc.description 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 -- 24 April 2019 through 26 April 2019 -- 148870 en_US
dc.description.abstract Melanoma which occurs with non-healing DNA degradation in melanocyte cells, is the most deadly type of skin cancers. Importantly, it can be identified for a treatment before it spreads to other tissues, i.e., early diagnosis. To identify, a specialist visually inspects whether the suspected lesion is melanoma or not. However, due to different education and experience levels of specialists or as a result of the patient not being in a facility that is specialized to this area, the problem of 'subjectivity' arises, and a good visual investigation accuracy may not always be achieved. Therefore, there is a significant need for automatic detection tools and systems. In this study, a method based on deep learning for automatic detection of melanoma from dermoscopic images is proposed. The developed system is tested with a large dataset and encouraging results are obtained. © 2019 IEEE. en_US
dc.identifier.doi 10.1109/EBBT.2019.8741934
dc.identifier.isbn 9.78E+12
dc.identifier.scopus 2-s2.0-85068548087
dc.identifier.uri https://doi.org/10.1109/EBBT.2019.8741934
dc.identifier.uri https://hdl.handle.net/20.500.14365/3522
dc.language.iso tr en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Convolutional neural networks en_US
dc.subject Deep learning en_US
dc.subject Dermoscopy en_US
dc.subject Melanoma en_US
dc.subject Skin cancer en_US
dc.subject Biomedical engineering en_US
dc.subject Deep learning en_US
dc.subject Deep neural networks en_US
dc.subject Diagnosis en_US
dc.subject Diseases en_US
dc.subject Electronic medical equipment en_US
dc.subject Large dataset en_US
dc.subject Neural networks en_US
dc.subject Oncology en_US
dc.subject Automatic Detection en_US
dc.subject Convolutional neural network en_US
dc.subject Dermoscopic images en_US
dc.subject Dermoscopy en_US
dc.subject Melanoma en_US
dc.subject Melanoma detection en_US
dc.subject Skin cancers en_US
dc.subject Visual investigation en_US
dc.subject Dermatology en_US
dc.title Deep Learning Based Melanoma Detection From Dermoscopic Images en_US
dc.title.alternative Dermoskopik Görüntülerden Derin Ö?renme Tabanli Melanom Tespiti en_US
dc.type Conference Object en_US
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gdc.description.departmenttemp Berkay, M., Department of Software Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Mergen, E.H., Department of Software Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Binici, R.C., Department of Software Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Bayhan, Y., Department of Computer Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Gungor, A., Department of Electrical and Electronics Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Okur, E., Department of Software Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Unay, D., Department of Biomedical Engineering, Izmir University of Economics, Izmir, 35330, Turkey; Turkan, M., Department of Electrical and Electronics Engineering, Izmir University of Economics, Izmir, 35330, Turkey en_US
gdc.description.endpage 4
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
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gdc.virtual.author Okur, Erdem
gdc.virtual.author Ünay, Devrim
gdc.virtual.author Türkan, Mehmet
gdc.virtual.author Türkan, Mehmet
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