Diagnosis of Lumbar Spondylolisthesis via Convolutional Neural Networks
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Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Spondylolisthesis, due to bilateral defects of the posterior vertebral arch, refers to a slippage of a vertebral body over another, usually with the superior vertebral body slipping anteriorly relative to an adjacent inferior vertebral body. The most common site for spondylolisthesis is L4 or L5. As with most spinal diseases, radiological findings are the main ingredients in diagnosing spondylolisthesis. Therefore, computer-Assisted systems can be used in diagnosing spondylolisthesis when adequate experience doctors in the outpatient clinics are not present. In this paper, we looked for a solution to the problem of diagnosis of spondylolisthesis by using two well-known artificial neural networks AlexNet and GoogleLeNet. The data set consists of 272 X-ray images in total. 136 of these images belong to patients suffering from spondylolisthesis, and 136 images without spondylolisthesis. Experimental results demonstrate that GoogleLeNet is 93.87% accuracy and performs slightly better than AlexNet with an accuracy of 91.67 %. © 2019 IEEE.
Açıklama
2019 International Conference on Artificial Intelligence and Data Processing Symposium, IDAP 2019 -- 21 September 2019 through 22 September 2019 -- -- 153040
Anahtar Kelimeler
Convolutional Neural Networks, Spondylolisthesis, Transfer Learning
Kaynak
2019 International Conference on Artificial Intelligence and Data Processing Symposium, IDAP 2019
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
