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人工智能辅助X线识别对骨科的应用价值研究进展
Hits: 2445   Download times: 1636   Received:February 19, 2020    
作者Author单位UnitE-Mail
薛冬 XUE Dong 锦州医科大学附属第一医院骨科, 辽宁 锦州 121000  
徐海林 XU Hai-lin 北京大学人民医院骨科, 北京 100000 Department of Orthopaedics, Peking University People's Hospital, Beijing 100000, China hailinxu66@qq.com 
王伟 WANG Wei 锦州医科大学附属第一医院骨科, 辽宁 锦州 121000
锦州医科大学骨外科学研究所, 辽宁 锦州 121000
 
期刊信息:《中国骨伤》2020年33卷,第9期,第887-890页
DOI:10.12200/j.issn.1003-0034.2020.09.019
成像作为评估肌肉骨骼病情的重要工具,从对疾病的患病风险评估到对疾病及病情进展的判断以及预后评分等均起到重要作用,伴随人工智能(artificial intellegence,AI)在图像检测和图像解释领域中的迅速发展,一些涉及肌肉骨骼X射线成像的AI辅助识别研究已经检验并显示了很高的潜在价值,可增强X射线成像价值链的各个部分,可通过提高成像效率、成像质量和诊断准确性对临床医生起指导性作用。目前,AI辅助成像识别技术发展仍处在早期阶段,AI算法需要进一步的提升和发展,影像数据仍不足且质量存在较大异质性,技术性能的长期准确性和稳定性需要进一步观察研究。
[关键词]:人工智能  图像处理,计算机辅助  X线  综述
 
Progress on artificial intelligence assisted X-ray film recognition in orthopedics
Abstract:As an important tool for assessing musculoskeletal conditions,imaging plays an important role in assessing the risk of disease,judging disease and the progress of disease,and prognosis scores. Accompanied with the rapid development of artificial intelligence (AI) in the field of image detection and interpretation,some AI-assisted recognition studies involving musculoskeletal X-ray imaging have been examined and shown a high potential value,which can enhance various parts of the X-ray imaging value chain and guide clinicians by improving imaging efficiency,imaging quality,and diagnostic accuracy. At present,the development of AI-assisted imaging recognition technology is still at an early stage. AI algorithms need to be further improved and developed. Image data is still insufficient and the quality is relatively heterogeneous. The long-term accuracy and stability of technical performance require further observation and research.
KEYWORDS:Artificial intelligence  Image processing,computer-assisted  X-rays  Review
 
引用本文,请按以下格式著录参考文献:
中文格式:薛冬,徐海林,王伟.人工智能辅助X线识别对骨科的应用价值研究进展[J].中国骨伤,2020,33(9):887~890
英文格式:XUE Dong,XU Hai-lin,WANG Wei.Progress on artificial intelligence assisted X-ray film recognition in orthopedics[J].zhongguo gu shang / China J Orthop Trauma ,2020,33(9):887~890
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