Derin öğrenme yöntemleriyle dermoskopi görüntülerinden melanom tespiti: Kapsamlı bir çalışma

Year 2019, Volume: 34 Issue: 4, 2241 - 2260, 25.06.2019

Oktay Yıldız

https://doi.org/10.17341/gazimmfd.435217

Cited By: 12

Abstract

Cilt
kanseri yaygın görülen ve tedavi edilmemesi durumunda ölüme neden olan ciddi
bir hastalıktır. Melanom ise nadir görülmesine rağmen ölüme en çok neden olan
cilt kanseri türüdür. Tüm hastalıklarda olduğu gibi cilt kanserinin erken ve
doğru tespit edilmesi hayati önem taşımaktadır.  Bilgisayar destekli tanı sistemleri cilt
kanseri tespitinde hekimlere ve hastalara yardımcı olabilir. Bilgisayar
destekli tanı sistemlerinde özellikle makine öğrenmesi ve derin öğrenme
algoritmaları etkin bir şekilde kullanılmaktadır. Gerçekleştirilen bu çalışmada
cilt kanseri türü olan melanom için otomatik tanı koyabilecek bir sistem
önerilmektedir. Melanom tanısı için tasarlanan C4Net derin sinir ağ modeli ile
beraber literatürde ön plana çıkmış AlexNet, GoogLeNet, ResNet, VGGNet derin
öğrenme algoritmaları ve Yapay sinir ağları, En yakın komşu algoritması ve
Destek vektör makinesi gibi geleneksel makine öğrenmesi algoritmalarını da
kapsayan detaylı bir deneysel çalışma yapılmıştır. Gerçekleştirilen deneysel
çalışmalarda melanom tanısı için tasarlanan C4Net derin sinir ağ modeli diğer
yöntemlere göre daha yüksek doğrulukta sınıflandırma başarısı göstermiştir. 

Keywords

melanom tespiti, konvolüsyonel sinir ağı, derin öğrenme, makine öğrenmesi, cilt kanseri

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