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Development of artificial intelligence in diagnosis and treatment of spinal diseases
ZHAO Weili  ZHANG Enlong  LIU Ke  WANG Qizheng  CHEN Yongye  YUAN Huishu  LANG Ning 

Cite this article as: Zhao WL, Zhang EL, Liu K, et al. Development of artificial intelligence in diagnosis and treatment of spinal diseases[J]. Chin J Magn Reson Imaging, 2022, 13(6): 160-163. DOI:10.12015/issn.1674-8034.2022.06.034.


[Abstract] Artificial intelligence mainly refers to machine learning, and deep learning is a specific type of mechine learning. The technologies in the field of artificial intelligence, especially the deep learning methods, have been widely used in medical image and big data processing, including image reconstruction, image processing, image analysis and model construction. By using the related methods of artificial intelligence, we can achieve the aim of location and segmentation of spinal structure, and the comprehensive analysis of spinal diseases, such as the diagnosis and differential diagnosis, clinical decision support and prognosis prediction, which provides the basis for the selection of the most reasonable treatment of spinal diseases.
[Keywords] artificial intelligence；deep learning；spine；vertebral fracture；spinal degenerative diseases；spinal tumor；spine deformity；diagnosis；treatment；prognosis prediction

ZHAO Weili1   ZHANG Enlong2   LIU Ke1   WANG Qizheng1   CHEN Yongye1   YUAN Huishu1   LANG Ning1*  

1 Department of Radiology, Peking University Third Hospital, Beijing 100191, China

2 Department of Radiology, Peking University International Hospital, Beijing 102206, China

Lang N, E-mail: 13501241339@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81971578); Natural Science Foundation of Beijing (No. Z190020).
Received  2022-03-11
Accepted  2022-04-24
DOI: 10.12015/issn.1674-8034.2022.06.034
Cite this article as: Zhao WL, Zhang EL, Liu K, et al. Development of artificial intelligence in diagnosis and treatment of spinal diseases[J]. Chin J Magn Reson Imaging, 2022, 13(6): 160-163. DOI:10.12015/issn.1674-8034.2022.06.034.

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