分子影像学杂志2025，Vol.48Issue(12)：1484-1490,7.DOI:10.12122/j.issn.1674-4500.2025.12.04
人工智能多任务模型在胎儿心脏超声标准切面识别与结构分割中的应用
Application of a multi-task AI model for standard plane recognition and structure segmentation in fetal cardiac ultrasound
摘要
Abstract
Objective To integrate artificial intelligence with prenatal ultrasound imaging by developing a deep-learning multi-task model that simultaneously identifies standard fetal cardiac planes and performs precise instance segmentation of key anatomical structures.Methods A total of 3312 fetal cardiac ultrasound images were collected from 1300 singleton pregnancies at 18-24 weeks of gestation in the Second Affiliated Hospital of Fujian Medical University from January 2021 to July 2023,and all images were jointly annotated by three associate chief sonographers.The dataset covers five standard cardiac planes,apical four-chamber(4CH),three-vessel(3VV),three-vessel-and-trachea(3VT),right ventricular outflow tract(RVOT)and left ventricular outflow tract(LVOT),together with ten critical structures,including the left/right ventricles,left/right atria,pulmonary artery,main pulmonary artery,ascending aorta,aorta,trachea and superior vena cava.YOLOv11 was adopted as the backbone network for instance segmentation.An additional classification branch was attached to the detection head to realize joint learning of plane recognition and structure segmentation.Results The proposed model achieved an AUC of 0.976 for plane recognition and an mAP of 0.937 for instance segmentation.Compared with single-task models performing only classification or segmentation,the multi-task framework demonstrated superior overall performance.Conclusion The YOLOv11-based multi-task learning model accurately recognizes standard fetal cardiac planes and delineates key anatomical structures,offering considerable potential to enhance the efficiency and accuracy of prenatal screening for congenital heart anomalies.关键词
胎儿心脏超声/标准切面识别/关键结构分割/多任务学习/YOLOv11/人工智能辅助诊断Key words
fetal cardiac ultrasound/standard plane recognition/key structure segmentation/multi-task learning/YOLOv11/AI-assisted diagnosis引用本文复制引用
李惠莲,李芙蓉,柳培忠,何韶铮..人工智能多任务模型在胎儿心脏超声标准切面识别与结构分割中的应用[J].分子影像学杂志,2025,48(12):1484-1490,7.基金项目
福建省科技创新联合资金项目(2024Y9392) （2024Y9392）
福建医科大学研究生教育教学研究项目(Y24013) （Y24013）
