中国现代医生2023，Vol.61Issue(36)：44-48,5.DOI:10.3969/j.issn.1673-9701.2023.36.011
基于AI技术的腰椎X射线图像质量控制模型的构建与应用
Construction and application of lumbar X-ray image quality control model based on AI technology
摘要
Abstract
Objective To establish a lumbar radiography image quality control model by using the deep learning algorithm and evaluate clinical images in real time and retrospectively based on the developed model.Methods The anteroposterior,lateral and oblique lumbar radiographs of 1389 patients collected between January 2018 to February 2021 at the The First Affiliated Hospital of Wenzhou Medical University were analyzed.The anatomical structures in the lumbar X-ray images were segmented using a full convolutional neural network based on U-Net,and the segmentation algorithm was utilized to establish an automatic evaluation model to detect substandard images.Dice similarity coefficient(DSC)was used to evaluate the performance of the model,and the lumbar radiography images were statistically evaluated after the application of the model.Results The accuracy of the model on the validation set was 0.971-0.990(0.98±0.10),the sensitivity was 0.714-0.933(0.86±0.13),and the specificity was 0.995-1.000(0.99±0.12).The quality control model had an excellent rate of 28.8%,an intermediate rate of 54.8%,and a failure rate of 16.4%for lumbar spine radiography in 2022.Conclusion The lumbar spine X-ray image quality control model based on artificial intelligence realizes accurate segmentation of lumbar spine anatomical structures and makes accurate evaluation of image quality,which is helpful to ensure the standardization of lumbar spine X-ray radiography operation by关键词
质量控制/数字X射线摄影/人工智能/图像分割/深度学习Key words
Quality control/Digital radiography/Artificial intelligence/Image segmentation/Deep learning分类
医药卫生引用本文复制引用
邓青山,陈晓,刘鑫淼,王强,陈磊,曹国全..基于AI技术的腰椎X射线图像质量控制模型的构建与应用[J].中国现代医生,2023,61(36):44-48,5.基金项目
浙江省温州市基础性科研项目(2020H0001) （2020H0001）
