Gu Yanjun, Wang Yinxiu, Li Mingxuan, Wang Ruideng
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.
Osteoporos Int. 2025 Aug 6. doi: 10.1007/s00198-025-07604-z.
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.
深度学习是一种模仿神经网络来构建决策模型的机器学习方法。计算能力和算法的最新进展增强了深度学习在医学成像中诊断椎体骨折的潜力。深度学习在椎体骨折诊断中的应用，包括椎体识别和椎体骨折类型分类，可能会显著减轻放射科医生和骨科医生的工作量，并大大提高椎体骨折诊断的准确性。在这篇叙述性综述中，我们将总结深度学习模型在椎体骨折诊断中的应用。
