Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods
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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
