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在糖尿病视网膜病的自动化非 perfusion 量化在超宽场扫描源 OCT 血管学上.

Tai Yong Loh1, Juling Sia1, Wei Hing Seah2

  • 1Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.

Ophthalmology science
|February 18, 2026
PubMed
概括

一个新的深度学习算法在超宽场扫描源OCTA (UWF SS-OCTA) 图像中准确地细分非 perfusion 区域 (NPA),帮助评估糖尿病视网膜病变 (DR) 的严重程度. 这项技术在DR中对客观生物标志物分析具有前景.

关键词:
自动图像分析自动化图像分析生物标志物 生物标志物卷积神经网络 (CNN) 是一种神经网络.深度学习是一种深度学习.糖尿病视网膜病变 - 糖尿病视网膜病变在眼科中,叶无血管区 (FAZ) 和人工智能.非 perfusion 区域 (NPA) 是一个非 perfusion 区域.不透指数 (NPI) 是指不透的指数.超广场扫描源光学连贯性断层扫描血管学 (UWF SS-OCTA)

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