Intelligent recognition and automatic measurement of uterine fibroids based on ultrasonic images
10.3760/cma.j.cn131148-20250122-00038
- VernacularTitle:基于超声图像的子宫肌瘤智能识别与长短径自动测量
- Author:
Yanhui ZHANG
1
;
Yi XIONG
;
Bo SHI
;
Xiaobing LIANG
;
Meilan CHEN
;
Kai WU
Author Information
1. 汕头大学医学院，汕头 515000
- Publication Type:Journal Article
- Keywords:
Uterine fibroids;
Ultrasound image;
Deep learning;
Ellipse fitting;
Automatic measurement
- From:
Chinese Journal of Ultrasonography
2025;34(7):602-607
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To develop an intelligent recognition and precise segmentation technique using ultrasonic images，and to enhance diagnostic efficiency and accuracy.Methods:A total of 1，430 patients diagnosed with uterine fibroids through transvaginal ultrasonography at the Maternal and Child Health Hospital of Guangming from November 2020 to October 2024 were retrospectively included. Ultrasonic images were manually annotated by two experienced physicians and reviewed by a senior expert. The Mask DINO deep learning model was used for lesion segmentation，and the segmentation results were optimized using ellipse fitting technology. Model performance was evaluated using the Dice coefficient，intraclass correlation coefficient（ICC），mean absolute error（MAE），and measurement accuracy.Results:In the test set of 286 cases，the average Dice coefficient of model prediction was 0.992，indicating extremely high segmentation accuracy. The average accuracy of lesion identification by the model was 0.909，with 241 correctly identified samples，19 basically correct samples，and 26 incorrect samples. In terms of long and short axis measurements，the ICC of the model's direct predictions were 0.871（short axis）and 0.784（long axis），with MAE of 0.436 cm（short axis）and 0.508 cm（long axis）. After optimization with ellipse fitting，the ICC increased to 0.893（short axis）and 0.866（long axis），and the MAE decreased to 0.191 cm（short axis）and 0.274 cm（long axis），the measurement accuracy improved significantly.Conclusions:The intelligent recognition and precise segmentation technique for uterine fibroids based on ultrasonic images constructed in this study performed excellently in lesion segmentation and measurement，it can significantly improve the efficiency and accuracy of diagnosis.
