结合深度学习和智能生物识别,提取超声波标准平面并评估早期妊娠周
Yuanyuan Pei1, Longjiang E1, Changping Dai2
1Clinical Data Center, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, China.
European radiology
|July 1, 2023
概括
这项研究引入了一种人工智能工具,用于自动化早期怀孕评估,通过超声波准确确定妊娠周. 该系统的性能优于人类超声波仪,减少了分析时间和潜在的错误.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 产科和妇科 产科和妇科
背景情况:
- 准确评估妊娠周对于早期怀孕管理至关重要.
- 手动超声波分析来确定妊娠约会可能耗时且容易变化.
- 需要自动化工具来提高产科超声波的效率和准确性.
研究的目的:
- 开发和验证一个完全自动化的AI系统,用于提取标准的超声波平面.
- 使用深度学习和生物识别自动评估早期妊娠周.
- 为了比较人工智能系统与人类超声波仪的性能.
主要方法:
- 一项对214个阴道超声视频进行的回顾性研究.
- 用于标准平面提取的自动框架分割和深度学习.
- 用于妊娠囊轮的细分模型和用于测量的自动化生物识别.
- 与中级和高级超声波专家对AI系统性能进行比较.
主要成果:
- 在标准平面提取中具有高精度 (AUC 0.975,灵敏度 0.961,特异性 0.979).
- 妊娠囊的准确细分 (mDice 0.974).
- 与超声波相比,人工智能系统的相对误差较低,妊娠周的评估更快.
结论:
- 开发的端到端人工智能工具自动化了怀孕早期怀孕周评估.
- 该系统有可能减少手动分析时间和测量误差.
- 这种人工智能工具可以优化超声波仪的资源,并提高早期怀孕评估的可靠性.
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