Diagnosis of Eye Retinal Diseases Based on Convolutional Neural Networks Using Optical Coherence Images

Sertkaya M. E., Ergen B., Togacar M.

23rd International Conference Electronics, ELECTRONICS 2019, Palanga, Litvanya, 17 - 19 Haziran 2019, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/electronics.2019.8765579
  • Basıldığı Şehir: Palanga
  • Basıldığı Ülke: Litvanya
  • Anahtar Kelimeler: Biomedical optical imaging, Convolutional neural networks, Medical diagnosis, Supervised learning
  • Samsun Üniversitesi Adresli: Hayır

Özet

In this study, the diagnosis of some diseases in the retina of the eye by using deep learning architectures is intended to be diagnosed. Optical Coherence Tomography device from Choroidal Neovascularization, Diabetic Macular Edema, Drusen and healthy eye retinal images were examined. LeNet, AlexNet and Vgg16 architectures of deep learning were used. In each architecture, the hyper parameters were changed to diagnose these diseases. Results of the implementation showed that exhibit successful results in Vgg16 and AlexNet architecture. Dropout layer structure in AlexNet has been shown to reduce the loss by minimizing loss.