自动明亮场涂抹显微镜用于诊断肺结核病
Mikaela Kalline Maciel Serrão1, Marly Guimarães Fernandes Costa1, Luciana Botinelly Mendonça Fujimoto2
1R&D Center in Electronic and Information Technology, Federal University of Amazonas, Manaus, 69067-005, Brazil.
Computers in biology and medicine
|March 10, 2024
概括
这项研究引入了第一个用于诊断肺结核 (TB) 的自动化方法,使用明亮场涂抹显微镜,与世卫组织分级尺度保持一致. 人工智能系统在检测和量化结核病菌以诊断结核病方面取得了很高的准确性.
科学领域:
- 医学诊断 医学诊断 医学诊断
- 计算机视觉 计算机视觉
- 生物医学成像技术 生物医学成像技术
背景情况:
- 肺结核 (TB) 诊断传统上依赖于手动唾液涂抹显微镜,这是劳动密集型和主观的.
- 现有的自动化方法主要集中在细菌检测上,而不是世界卫生组织 (WHO) 所要求的全面诊断分级.
- 肺结核的准确和自动诊断对于及时治疗和疾病控制至关重要.
研究的目的:
- 开发和评估第一个完全自动化的肺结核诊断方法,使用明亮场涂抹显微镜.
- 实施一个符合世卫组织细菌量化五分级的系统.
- 通过人工智能提高结核病诊断的客观性和效率.
主要方法:
- 一种新的方法,将基于深度神经网络的语义细分与颜色和形状过相结合,用于假阳性减少.
- 在深度神经网络中评估不同的编码器配置,利用深度可分离的卷积层和道注意力机制.
- 在一个大型,定制注释的数据集上测试系统,包括所有5个世卫组织结核病诊断类别的250个测试集.
主要成果:
- 该自动化系统在肺结核诊断方面实现了0.894的平均精度.
- 自动诊断系统的平均召回值为0.896.
- 总体平均F1得分为0.895,在所有诊断类别中表现强.
结论:
- 拟议的自动化方法提供了一种可靠和客观的方法,通过涂抹显微镜诊断肺结核.
- 这种人工智能驱动的系统有可能显著提高诊断效率和准确性,支持全球结核病控制工作.
- 该方法遵循世卫组织分级尺度,确保了临床相关性和与传统诊断程序的可比性.
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