基于色带融合的视网膜图像中央凹自动检测

R. Veras, F. Medeiros, Romuere R. V. Silva, K. Aires
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引用次数: 5

摘要

提出了一种彩色视网膜图像中央凹检测的新方法。这种解剖结构的自动检测是计算机辅助诊断黄斑变性等几种视网膜疾病的先决条件。该算法通过确定感兴趣区域(ROI),并考虑视盘(OD)坐标以及中心区域(即中央凹)是一个没有血管的均匀黑暗区域的事实来检测黄斑中心。我们的分割算法在增强图像中搜索最低平均颜色强度窗口,该窗口由红色和绿色通道之间的融合产生。然后,在三个公共基准数据库上进行测试,共包含254张图像。
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Automatic Detection of Fovea in Retinal Images Using Fusion of Color Bands
This paper presents a new method for fovea detection in color retinal images. Automatic detection of this anatomical structure is a prerequisite for computer aided diagnosis of several retinal diseases, such as macular degeneration. The proposed algorithm detects the macula center by determining a region of interest (ROI) and taking into account optic disk (OD) coordinates and the fact that the central region, i.e. fovea, is a homogenous dark area without blood vessels. Our segmentation algorithm searches for the lowest mean color intensity window in the enhanced image that results from a fusion between the red and green channels. Then, tests were carried on three public benchmark databases, which constitute a total of 254 images.
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