Pseudopapilledema diagnosis based on a hybrid approach using deep transfer learning - DURU, ADİL DENİZ (My University, 2023)
This Papilledema is edema caused by elevated pressure inside the brain near the area that leads the optic nerve to reach the eye. If left untreated, this condition can cause severe difficulties, for instance, aberrant optical changes, reduced sharpness of vision, and irreversible blindness. At present, an approach based on image processing for determining the degree of papilledema from color fundus images was given utilizing transfer learning approaches. The used dataset here contains 295 papilledema images, 295 pseudopapilledema images, and 779 control images. For the image preparation, a segmentation optimizer was utilized. The performance of the transfer learning techniques GoogleNet, MobileNetV2, ResNet-18, and ResNet-50 was then compared. Furthermore, Sensitivity and specificity and constructed ROC curves were calculated. The ResNet-50 employing the optimizer ADAM method performed best in the testing, with 98% total accuracy. The findings of the studies demonstrated that a combination of segmentation, optimization models, and transfer learning techniques may be utilized to determine the severity of papilledema automatically. The total accuracy was higher when compared to other similar studies described in the literature.
Keywords: Bilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği; Kontrol ve Sistem Mühendisliği; Bilgisayar Bilimleri; Algoritmalar; Mühendislik ve Teknoloji; Information Systems, Communication and Control Engineering; Control and System Engineering; Computer Sciences; algorithms; Engineering and Technology; Mühendislik, Bilişim ve Teknoloji (ENG); Bilgisayar Bilimi; Mühendislik; OTOMASYON & KONTROL SİSTEMLERİ; BİLGİSAYAR BİLİMİ, YAPAY ZEKA; MÜHENDİSLİK, İMALAT; Engineering, Computing & Technology (ENG); COMPUTER SCIENCE; ENGINEERING; AUTOMATION & CONTROL SYSTEMS; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; ENGINEERING, MANUFACTURING; Yapay Zeka; Fizik Bilimleri; Bilgisayar Bilimi Uygulamaları; Bilgisayarla Görme ve Örüntü Tanıma; Endüstri ve İmalat Mühendisliği; Kontrol ve Optimizasyon; Artificial Intelligence; Physical Sciences; Computer Science Applications; Computer Vision and Pattern Recognition; Industrial and Manufacturing Engineering; Control and Optimization; googlenet; mobilenetv2; papilledema; pseudopapilledema; resnet-18; resnet-50