Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods
Yükleniyor...
Dosyalar
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Turkish Joint Diseases Foundation
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Objectives: In this study, we aimed to differentiate normal cervical graphs and graphs of diseases that cause mechanical neck pain by using deep convolutional neural networks (DCNN) technology. Materials and methods: In this retrospective study, the convolutional neural networks were used and transfer learning method was applied with the pre-trained VGG-16, VGG-19, Resnet-101, and DenseNet-201 networks. Our data set consisted of 161 normal lateral cervical radiographs and 170 lateral cervical radiographs with osteoarthritis and cervical degenerative disc disease. Results: We compared the performances of the classification models in terms of performance metrics such as accuracy,
Açıklama
Anahtar Kelimeler
Cervical radiography; convolutional neural network; deep; learning; disc space narrowing; osteoarthritic changes; transfer learning
Kaynak
Joint Diseases and Related Surgery
WoS Q Değeri
Q3
Scopus Q Değeri
Q2
Cilt
33
Sayı
1
