Aid to the medical diagnosis by retinal analysis

Kahina Boucherk, Z. Ameur, Maï K. Nguyen
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Abstract

To diagnose serious eyes diseases, ophthalmologists use the color retinal images of a patient acquired from the digital fundus camera, such as the diabetic retinopathy that affects the morphology of the blood vessels tree, so an automatic detection and extraction of blood vessels in retinal images is important. In this paper, we present a method to extract blood vessels and delineate vascular intersection and crossovers. The proposed algorithm consists of three steps: first, the appearance of the blood vessels is enhanced and background noise is suppressed using Gaussian filters, in second step, entropic thresholding is used to detecting pixels in the enhanced image. Finally, the vascular intersections and bifurcations are obtained via the crossing number (CN) technique.
通过视网膜分析帮助医学诊断
为了诊断严重的眼部疾病,眼科医生使用从数字眼底相机获取的患者彩色视网膜图像,例如糖尿病视网膜病变影响血管树的形态,因此视网膜图像中血管的自动检测和提取非常重要。在本文中,我们提出了一种提取血管和描绘血管相交和交叉的方法。该算法包括三个步骤:首先,对血管的外观进行增强,并使用高斯滤波器抑制背景噪声;第二步,使用熵阈值法检测增强图像中的像素点。最后,通过交叉数(CN)技术得到了维管的交叉点和分支。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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