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Segmentation of Foveal Avascular Zone of the Retina Based on Morphological Alternating Sequential Filtering

机译:基于形态学交替顺序滤波的视网膜中央凹无血管区域的分割

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The non-invasive visualization of retinal microvasculature is a traditional way to diagnose and predict some diseases. The region of foveal avascular zone (FAZ) is an important tool to quantify the macular ischemic with implications in the visual acuity. In this work, we proposed an automatic segmentation of FAZ using high-resolution retinal images captured by a retinography conjugated to Retinal Function Imager (RFI) apparatus. The pixels corresponding to FAZ are automatically detected, segmented and measured (area, perimeter, height and width). The proposed algorithm was tested with 20 images of 10 healthy volunteers, and the results were compared to three manual segmentations. The difference between the software and the manual segmentation was 12.8930% (the mean difference between humans was 7.8288%), and the time of each image segmentation was performed 14.1549 times faster by the computer. The method obtained accuracy of 0.9947, sensitivity of 0.8442, and specificity of 0.9972.
机译:视网膜微脉管系统的非侵入性可视化是诊断和预测某些疾病的传统方法。中心凹无血管区域(FAZ)是量化黄斑缺血的重要工具,对视敏度有影响。在这项工作中,我们提出了使用高分辨率的视网膜图像对FAZ进行自动分割的方法,该高分辨率的视网膜图像是由与视网膜功能成像仪(RFI)装置共轭的视网膜成像所捕获的。自动检测,分割和测量与FAZ对应的像素(面积,周长,高度和宽度)。该算法对10名健康志愿者的20张图像进行了测试,并将结果与​​3种手动分割方法进行了比较。该软件与手动分割之间的差异为12.8930%(人与人之间的平均差异为7.8288%),并且每次图像分割的时间由计算机执行的速度为14.1549倍。该方法的准确度为0.9947,灵敏度为0.8442,特异性为0.9972。

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