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在视网膜底部成像中进行最佳无otropic引导过:增强和细分的双重方法

G Tirumala Vasu¹, Samreen Fiza², Subba Rao Polamuri³

¹Innovation & Translational Research Hub, Department of Electronics & Communications Engineering, Presidency University, Bangalore, Karnataka, India.

|July 31, 2025

概括

本研究介绍了用于视网膜血管细分和增强的最佳无otropic引导过 (OAGF). OAGF框架通过增强视网膜图像和细分血管来改善系统性疾病的检测.

科学领域:

医疗成像医学成像
眼科医生眼科眼科
计算机视觉计算机视觉

背景情况:

视网膜为系统性疾病检测提供了微循环的非侵入性观察.
传统的视网膜图像分析方法与文物和边缘保存作斗争.

研究的目的:

为统一的视网膜血管增强和细分引入一个最佳无otropic引导过 (OAGF) 框架.
解决视网膜图像分析现有方法的局限性.

主要方法:

这是一个三阶段的方法,包括照明校正,YCbCr转换和OAGF处理.
优化了顶帽转换和同型过以进行细分.
对于增强的图像,将其转换回RGB.

主要成果:

在DRIVE和STARE数据集上,OAGF方法论表现出卓越的性能.
获得了高的子系数 (0.860,0.854),精度 (0.845,0.834) 和F1分数 (0.827,0.817).

结论:

OAGF框架为视网膜底图像提供了有效的增强和细分.
优于当前的算法,为早期疾病检测提供了一个有前途的工具.

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