Investigating post-processing of scanning laser ophthalmoscope images for unsupervised retinal blood vessel detection

Gavin Robertson, E. Pellegrini, C. Gray, E. Trucco, T. MacGillivray
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引用次数: 4

Abstract

We explore post-processing of scanning laser ophthalmoscope (SLO) images for the automatic detection of retinal blood vessels. The retinal vasculature is first enhanced using morphological and Gaussian matched filters before a thresholding technique produces a binary vessel map. Such permutations of post-processing techniques are commonly used to achieve unsupervised classification of the vasculature in fundus images, and it is the purpose of this study to investigate their applicability to SLO imaging. We compare the results of vascular detection as performed on SLO and fundus images.
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研究激光检眼镜扫描图像在无监督视网膜血管检测中的后处理
本文探讨了激光检眼镜扫描图像的后处理方法,以实现视网膜血管的自动检测。在阈值化技术生成二值血管图之前,首先使用形态学和高斯匹配滤波器增强视网膜血管。这种后处理技术的排列通常用于眼底图像中血管系统的无监督分类,本研究的目的是研究其在SLO成像中的适用性。我们比较了SLO和眼底图像的血管检测结果。
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