人工智能在胎儿心脏超声图像 VSD 产前诊断中的应用。

IF 2.8 2区 医学 Q1 OBSTETRICS & GYNECOLOGY
Furong Li, Ping Li, Zhonghua Liu, Shunlan Liu, Pan Zeng, Haisheng Song, Peizhong Liu, Guorong Lyu
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引用次数: 0

摘要

背景:开发人工智能(AI)与超声成像相结合的方法,为胎儿心脏室间隔缺损(VSD)提供准确、客观、高效的辅助诊断方法。方法:2016年1月至2022年6月期间,对500名孕妇的1451张胎儿心脏超声图像进行了综合分析。人工标记胎儿心脏区域,并由专家判别是否存在 VSD。在训练集中遵循五次交叉验证原则,以开发辅助诊断 VSD 的人工智能模型。在测试集中使用 mAP@0.5、精确度、召回率和 F1 分数等指标对模型进行评估。诊断准确率和推理时间也与初级医生、中级医生和高级医生进行了比较:人工智能模型诊断 VSD 的 mAP@0.5、精确度、召回率和 F1 分数分别为 0.926、0.879、0.873 和 0.88。在该系统的帮助下,初级医生和中级医生的准确率分别提高了 6.7% 和 2.8%:本研究报告了一种人工智能辅助诊断 VSD 的方法,该方法与人工识别具有很高的一致性。同时,它的参数数量和计算复杂度较低,也能提高一些医生对 VSD 的诊断准确性和速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of artificial intelligence in VSD prenatal diagnosis from fetal heart ultrasound images.

Background: Developing a combined artificial intelligence (AI) and ultrasound imaging to provide an accurate, objective, and efficient adjunctive diagnostic approach for fetal heart ventricular septal defects (VSD).

Methods: 1,451 fetal heart ultrasound images from 500 pregnant women were comprehensively analyzed between January 2016 and June 2022. The fetal heart region was manually labeled and the presence of VSD was discriminated by experts. The principle of five-fold cross-validation was followed in the training set to develop the AI model to assist in the diagnosis of VSD. The model was evaluated in the test set using metrics such as mAP@0.5, precision, recall, and F1 score. The diagnostic accuracy and inference time were also compared with junior doctors, intermediate doctors, and senior doctors.

Results: The mAP@0.5, precision, recall, and F1 scores for the AI model diagnosis of VSD were 0.926, 0.879, 0.873, and 0.88, respectively. The accuracy of junior doctors and intermediate doctors improved by 6.7% and 2.8%, respectively, with the assistance of this system.

Conclusions: This study reports an AI-assisted diagnostic method for VSD that has a high agreement with manual recognition. It also has a low number of parameters and computational complexity, which can also improve the diagnostic accuracy and speed of some physicians for VSD.

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来源期刊
BMC Pregnancy and Childbirth
BMC Pregnancy and Childbirth OBSTETRICS & GYNECOLOGY-
CiteScore
4.90
自引率
6.50%
发文量
845
审稿时长
3-8 weeks
期刊介绍: BMC Pregnancy & Childbirth is an open access, peer-reviewed journal that considers articles on all aspects of pregnancy and childbirth. The journal welcomes submissions on the biomedical aspects of pregnancy, breastfeeding, labor, maternal health, maternity care, trends and sociological aspects of pregnancy and childbirth.
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