Preliminary study on the construction of an echocardiogram image quality control system based on artificial intelligence
10.3760/cma.j.cn131148-20240823-00456
- VernacularTitle:超声心动图图像人工智能质控系统构建研究
- Author:
Zhanru QI
1
;
Hanlin CHENG
;
Chunjie SHAN
;
Ruiyang CHEN
;
Hexiang WENG
;
Yue DU
;
Guanjun GUO
;
Xiaoxian WANG
;
Jing YAO
;
Shouhua LUO
;
Aijuan FANG
;
Hui CHEN
;
Zhongqing SHI
Author Information
1. 南京大学医学院附属鼓楼医院超声医学科 南京大学医学院附属鼓楼医院医学影像中心，南京 210008
- Publication Type:Journal Article
- Keywords:
Echocardiography;
Artificial intelligence;
Image quality control;
Apical view
- From:
Chinese Journal of Ultrasonography
2025;34(2):107-113
- CountryChina
- Language:Chinese
-
Abstract:
Object:To explore the feasibility of using artificial intelligence for quality control of echocardiographic images.Methods:Retrospectively，5 000 two-dimensional echocardiographic video images within the period from 2021 to 2023 were randomly retrieved from the echocardiography database of Nanjing Drum Tower Hospital，Affiliated Hospital of Medical School，Nanjing University. Among these selected images，1 559 of them were apical views. The physician team formulated the scoring rules，which specifically included four scoring criteria：gain，scaling ratio，cardiac axis angle，and structure. Subsequently，the data were labeled with view classification and image quality scores. The labeled data were further partitioned into the training set（ n = 643），the validation set（ n = 276），and the test set（ n = 640）. The training and validation sets were utilized for constructing the models for view classification and quality assessment，while the test set was employed to verify the models' effectiveness. The view classification module was implemented using the SlowFast model，and the quality assessment module involved algorithms such as ResNet，Video Swin Transformer，SSD，and U-Net. Results:The average accuracy，precision，recall rate and F1 score of the classification model in identifying each apical view were 0.987 1，0.983 0，0.987 1 and 0.984 9 respectively，and the inference time was（333.4 ± 105.4）ms. The average accuracies of the quality assessment module in terms of gain，scaling ratio，cardiac axis angle and display of main structures were 0.915 1，0.928 2，0.938 7 and 0.965 6 respectively，and the overall scoring accuracy was 0.912 7.Conclusions:The echocardiogram quality control system developed in this research can effectively classify and evaluate the quality of two-dimensional images of the apical views in echocardiograms. Moreover，it guarantees the objectivity，timeliness and high-efficiency of quality control，which has reference value for the establishment of the echocardiogram quality control system.
