Current applications of deep learning in vertebral fracture diagnosis.
Authors
Gu Y,Wang Y,Li M,Wang R
Affiliations (5)
Affiliations (5)
- Department of Pediatrics, Changshan County Maternal and Child Health Hospital, Quzhou, China.
- Department of Traditional Chinese Medicine, Changshan County Maternal and Child Health Hospital, Quzhou, China.
- School of Information and Electronics, Beijing Institute of Technology, Beijing, China. [email protected].
- Department of Orthopedics, Peking University Third Hospital, Beijing, China. [email protected].
- Engineering Research Center of Bone and Joint Precision Medicine, Beijing, China. [email protected].
Abstract
Deep learning is a machine learning method that mimics neural networks to build decision-making models. Recent advances in computing power and algorithms have enhanced deep learning's potential for vertebral fracture diagnosis in medical imaging. The application of deep learning in vertebral fracture diagnosis, including the identification of vertebrae and classification of vertebral fracture types, might significantly reduce the workload of radiologists and orthopedic surgeons as well as greatly improve the accuracy of vertebral fracture diagnosis. In this narrative review, we will summarize the application of deep learning models in the diagnosis of vertebral fractures.
Topics
Journal ArticleReview