Diagnosis of Osteoarthritic Changes, Loss of Cervical Lordosis, and Disc Space Narrowing on Cervical Radiographs With Deep Learning Methods

Tokdemir, GulUreten, KemalAtalar, EbruDuran, SemraMaras, HakanMaras, Yuksel2024-03-052025-09-182024-03-052025-09-182022Maraş, Yüksel;...et.al. (2022). "Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods", Joint Diseases and Related Surgery, Vol.33, No.1, pp.93-101.2687-47842687-4792https://doi.org/10.52312/jdrs.2022.445https://hdl.handle.net/20.500.12416/14801Maras, Yuksel/0000-0001-9319-0955; Duran, Semra/0000-0003-0863-2443; Tokdemir, Gul/0000-0003-2441-3056Objectives: 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,eninfo:eu-repo/semantics/openAccessDisc Space NarrowingOsteoarthritic ChangesTransfer LearningCervical RadiographyConvolutional Neural NetworkDeepLearningDiagnosis of Osteoarthritic Changes, Loss of Cervical Lordosis, and Disc Space Narrowing on Cervical Radiographs With Deep Learning MethodsDiagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methodsArticle10.52312/jdrs.2022.4452-s2.0-85127383643