Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3522
Title: Deep learning based melanoma detection from dermoscopic images
Other Titles: Dermoskopik görüntülerden derin ö?renme tabanli melanom tespiti
Authors: Berkay M.
Mergen E.H.
Binici R.C.
Bayhan Y.
Gungor A.
Okur E.
Unay D.
Keywords: Convolutional neural networks
Deep learning
Dermoscopy
Melanoma
Skin cancer
Biomedical engineering
Deep learning
Deep neural networks
Diagnosis
Diseases
Electronic medical equipment
Large dataset
Neural networks
Oncology
Automatic Detection
Convolutional neural network
Dermoscopic images
Dermoscopy
Melanoma
Melanoma detection
Skin cancers
Visual investigation
Dermatology
Publisher: Institute of Electrical and Electronics Engineers Inc.
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.
Description: 2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 -- 24 April 2019 through 26 April 2019 -- 148870
URI: https://doi.org/10.1109/EBBT.2019.8741934
https://hdl.handle.net/20.500.14365/3522
ISBN: 9.78173E+12
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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