基于YOLOv8的系统用于在单板计算机上检测指甲毛细血管
Seda Arslan Tuncer1, Muhammed Yildirim2, Taner Tuncer3
1Faculty of Engineering, Software Engineering, Firat University, 23119 Elazığ, Turkey.
Diagnostics (Basel, Switzerland)
|September 14, 2024
概括
这项研究引入了使用YOLOv8s进行客观指甲毛细血管分析的AI系统,有助于早期诊断全身性硬化和雷诺氏病.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 皮肤病学 皮肤病学
背景情况:
- 指甲毛细管镜检查识别了毛细管的变化,对于诊断全身性硬化和雷诺氏病至关重要.
- 手动毛细管镜分析是主观的,耗时的,并产生不一致的结果.
- 需要客观和有效的方法来评估毛细血管形态 (直径,密度等). ) 的情况.
研究的目的:
- 开发和评估基于人工智能的系统,用于自动化指甲床毛细血管检测.
- 量化毛细血管的数量,厚度和密度,以提高诊断准确度.
- 为了克服手动毛细管镜评估的局限性.
主要方法:
- 一个基于YOLOv8s的人工智能系统被开发出来.
- 该系统分析了记录的指甲床毛细血管的显微镜图像.
- 它使用单板计算机 (SBC) 上的数据库系统和软件.
主要成果:
- 人工智能系统的平均平均精度 (mAP) 为0.882.
- 毛细血管检测的F1得分为0.83.
- 该系统在检测毛细血管的数量,厚度和密度方面表现出良好的能力.
结论:
- 拟议的AI系统提供客观和高效的指甲毛细管分析.
- 它显示了改善系统性硬化和雷诺病的早期诊断和监测的前景.
- 自动毛细管镜检查可以提高诊断的一致性,减少劳动力.
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