Abstract

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Title:: Advances in artificial intelligence technology for parameter measurement in lumbar X-ray photograph

Author(s):: YAO Hongyan1; DENG Xing1; 3; CHEN Xiaofei2; WANG Wenqi2; ZHOU Sheng2; 1. The First Clinical Medical School of Gansu University of Chinese Medicine, Lanzhou 730000, China 2. Department of Medical Imaging, Gansu Provincial Hospital of TCM, Lanzhou 730050, China 3. Department of Interventional Radiology, Nanchong Central Hospital, Nanchong 637000, China

Keywords:: Keywords: low back pain lumbar X-ray deep learning artificial intelligence review

Abstract:: Abstract: Low back pain (LBP) is a prevalent public health problem worldwide, but the visual analysis and subjective judgment of lumbar spine X-ray photographs by clinicians no longer meet the demands for clinical precision and quantification of diagnosis and treatment. In recent years, the flourishing development of artificial intelligence (AI) and big data technology has provided conditions and foundations for intelligent detection and quantitative analysis of medical images. The establishment of models such as artificial neural networks, support vector machines and convolutional neural networks and the improvement of algorithms made the quantitative analysis and diagnosis of lumbar spine X-ray photographs possible. The cross-integration of AI technology with medical images has a promising application in reducing the workload of clinicians, effectively decreasing or eliminating manual measurement errors, and assisting clinicians in assessing spinal deformities and other related diseases more objectively from a quantitative perspective. At present, the development of AI technology-assisted diagnosis of lumbar spine diseases is still at an early stage, and the improvement of AI algorithms, the establishment of high-quality databases and the development of new criteria for parameter quantification need to be further explored.