Construction and application of lumbar X-ray image quality control model based on AI technology
10.3969/j.issn.1673-9701.2023.36.011
- VernacularTitle: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
- Author:
Qingshan DENG
1
;
Xiao CHEN
;
Xinmiao LIU
;
Qiang WANG
;
Lei CHEN
;
Guoquan CAO
Author Information
1. 温州医科大学附属第一医院放射科,浙江温州 325015
- Keywords:
Quality control;
Digital radiography;
Artificial intelligence;
Image segmentation;
Deep learning
- From:
China Modern Doctor
2023;61(36):44-48
- CountryChina
- Language:Chinese
-
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
