早期糖尿病角膜病变中角膜神经结构异常的AI辅助检测:深度学习框架的开发和验证
Jiali Pan1, Xiaoshuo Shi1, Longbiao Wan2
1Eye Center, Remin Hospital of Wuhan University, Wuhan, 430060, China.
Scientific reports
|January 20, 2026
概括
一个新的深度学习模型准确地检测到角膜微神经瘤在体内共聚焦显微镜图像中. 这种人工智能工具显著提高了初级医生的诊断准确性和效率,有助于评估糖尿病角膜神经病变.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 糖尿病角膜神经病变是一种糖尿病的并发症.
- 早期发现角膜微神经瘤对于治疗糖尿病角膜神经病变至关重要.
- 体内共聚焦显微镜 (IVCM) 是一种用于可视化角膜结构的成像技术.
研究的目的:
- 开发一个深度学习 (DL) 模型,从IVCM图像中自动检测和分类角膜微神经瘤.
- 评估DL模型在诊断糖尿病角膜神经病变方面的临床实用性.
主要方法:
- 一项回顾性研究,使用293名患者的4,554张IVCM图像进行培训和内部测试.
- 对87名患者的506张IVCM图像进行了外部验证.
- 该DL模型包括自动图像质量评估,微神经瘤检测和亚型分类.
主要成果:
- DL模型在图像质量选中实现了97.5%的准确性.
- 微神经瘤检测准确度为83.7% (内部) 和81.2% (外部).
- 模型辅助使初级医生的诊断准确度从68.7%提高到87.5%,阅读效率提高了2.2倍.
结论:
- 一个基于DL的系统可以自动分析IVCM图像以检测角膜微神经瘤.
- 该模型在独立数据集上展示了强大的性能.
- 人工智能工具显著提高了诊断准确性和效率,为临床医生评估糖尿病角膜神经病变.
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