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首页> 外文期刊>Journal of Digital Imaging >Detection of Neovascularization in Diabetic Retinopathy
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Detection of Neovascularization in Diabetic Retinopathy

机译：糖尿病性视网膜病变中新血管形成的检测

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摘要

Diabetic retinopathy has become an increasingly important cause of blindness. Nevertheless, vision loss can be prevented from early detection of diabetic retinopathy and monitor with regular examination. Common automatic detection of retinal abnormalities is for microaneurysms, hemorrhages, hard exudates, and cotton wool spot. However, there is a worse case of retinal abnormality, but not much research was done to detect it. It is neovascularization where new blood vessels grow due to extensive lack of oxygen in the retinal capillaries. This paper shows that various combination of techniques such as image normalization, compactness classifier, morphology-based operator, Gaussian filtering, and thresholding techniques were used in developing of neovascularization detection. A function matrix box was added in order to classify the neovascularization from natural blood vessel. A region-based neovascularization classification was attempted as a diagnostic accuracy. The developed method was tested on images from different database sources with varying quality and image resolution. It shows that specificity and sensitivity results were 89.4% and 63.9%, respectively. The proposed approach yield encouraging results for future development.
机译：糖尿病性视网膜病已成为失明的越来越重要的原因。尽管如此，可以通过早期发现糖尿病性视网膜病来预防视力下降，并通过定期检查进行监测。常见的视网膜异常自动检测是微动脉瘤，出血，硬性渗出液和棉斑。但是，视网膜异常的情况更糟，但是并没有进行太多研究来检测它。在新生血管中，由于视网膜毛细血管中氧气的大量缺乏，新血管得以生长。本文显示了图像归一化，紧密度分类器，基于形态学的算子，高斯滤波和阈值技术等各种技术的组合被用于开发新血管化检测技术。添加了一个功能矩阵框，以便对来自天然血管的新血管形成进行分类。尝试基于区域的新血管形成分类作为诊断的准确性。在不同质量和图像分辨率的不同数据库来源的图像上对开发的方法进行了测试。结果表明，特异性和敏感性结果分别为89.4％和63.9％。提议的方法为未来的发展带来了令人鼓舞的结果。

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