Classification of skin lesions using convolutional neural networks

Bilginer, Onur; Tunga, Burcu; Demirer, Rustu

doi:10.5505/pajes.2021.68700

Classification of skin lesions using convolutional neural networks

PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, cilt.28, sa.2, ss.208-214, 2022 (ESCI)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 28 Sayı: 2
Basım Tarihi: 2022
Doi Numarası: 10.5505/pajes.2021.68700
Dergi Adı: PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI
Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
Sayfa Sayıları: ss.208-214
Anahtar Kelimeler: Classifications of skin lesions, Hilbert transform, High dimensional model representation, CANCER
İstanbul Teknik Üniversitesi Adresli: Evet

Özet

In this paper we classified 4 skin lesions (Melanoma,Melanocytic Nevus, Basal Cell Carcinoma, Benign keratosis) from ISIC 2019 dataset which was published by International Skin Imaging Collabration in 2019. We used InceptionV3 convolutional neural network model for classification. We applied two preprocessing methods: High Dimensional Model Representation (HDMR) and Hilbert Transform. In conclusion we obtained 89% accuracy on classification of Basal Cell Carcinoma using Hilbert Transform. Moreover, we obtained 78% accuracy on classification of Melanoma using Contrast Enhancement High Dimensional Model Representation (HDMR).