Applications of Machine Learning to Imaging of Spinal Disorders: Current Status and Future Directions

被引:10
|
作者
Merali, Zamir A. [1 ]
Colak, Errol [2 ]
Wilson, Jefferson R. [1 ,3 ]
机构
[1] Univ Toronto, Dept Surg, Toronto, ON, Canada
[2] Univ Toronto, St Michaels Hosp, Dept Med Imaging, 30 Bond St, Toronto, ON M5B 1W8, Canada
[3] St Michaels Hosp, Dept Neurosurg, Toronto, ON, Canada
关键词
cervical; lumbar; thoracic; MRI; degenerative; OSTEOPOROTIC VERTEBRAL FRACTURES; AUTOMATED DETECTION; THORACOLUMBAR SPINE; NEURAL-NETWORKS; LUMBAR SPINE; CLASSIFICATION; CT; DEGENERATION; METASTASES;
D O I
10.1177/2192568220961353
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Study Design: Narrative review. Objectives: We aim to describe current progress in the application of artificial intelligence and machine learning technology to provide automated analysis of imaging in patients with spinal disorders. Methods: A literature search utilizing the PubMed database was performed. Relevant studies from all the evidence levels have been included. Results: Within spine surgery, artificial intelligence and machine learning technologies have achieved near-human performance in narrow image classification tasks on specific datasets in spinal degenerative disease, spinal deformity, spine trauma, and spine oncology. Conclusion: Although substantial challenges remain to be overcome it is clear that artificial intelligence and machine learning technology will influence the practice of spine surgery in the future.
引用
收藏
页码:23S / 29S
页数:7
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