Current applications of deep learning in vertebral fracture diagnosis.

Journal: Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Published Date:

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.

Authors

  • Yanjun Gu
    Department of Pediatrics, Changshan County Maternal and Child Health Hospital, Quzhou, China.
  • Yinxiu Wang
    Department of Traditional Chinese Medicine, Changshan County Maternal and Child Health Hospital, Quzhou, China.
  • Mingxuan Li
    College of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, PR China.
  • Ruideng Wang
    Department of Orthopedics, Peking University Third Hospital, Beijing, China. wangrd1314@163.com.

Keywords

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