基于改进的YOLOv5的自动指甲毛细血管密度测量方法
Hao Yin1, Zhiwei Wu1, An Huang2
1School of Physics and Optoelectronic Engineering, Foshan University, Foshan 528000, China.
Microvascular research
|August 15, 2023
概括
这项研究引入了一种使用改进的YOLOv5算法的自动化方法,用于从临床图像中准确测量指甲毛细血管密度. 新技术增强了对指甲状况的客观分析,改进了现有的方法.
科学领域:
- 生物医学工程 生物医学工程
- 医学成像分析 医学成像分析
- 生理学 生理学 生理学
背景情况:
- 爪毛细血管密度对于评估爪健康至关重要.
- 目前对指甲折叠图像的临床分析往往是主观的.
- 需要客观和快速的测量方法.
研究的目的:
- 开发一种用于测量指甲毛细血管密度的自动化方法.
- 为了提高指甲折形象分析的准确性和效率.
- 为临床医生提供一个客观的工具.
主要方法:
- 使用了一种改进的You Only Look Once版本5 (YOLOv5) 算法.
- 纳入了包括9mosaic和空间金字塔聚合在内的新技术.
- 用90度密度计算方法检测和过远端毛细血管.
主要成果:
- 拟议的自动化方法实现了85.2%的平均精度 (AP@0.5).
- 这比原来的YOLOv5,YOLOv6和R-CNN方法有了显著的改进.
- 结果显示与专家手工计算的高度一致.
结论:
- 改进的YOLOv5算法为自动化指甲毛细血管密度测量提供了有效和快速的解决方案.
- 这种自动化方法提高了指甲健康评估的客观性和准确性.
- 该方法显示优于现有的自动化技术和人工专家分析.
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