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A New Method for Automatic Detection and Diagnosis of Retinopathy Diseases in Colour Fundus Images Based on Morphology

机译:一种新方法,用于基于形态学的彩色眼镜图像视网膜病变疾病的自动检测和诊断

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Automatic detection of lesions in retinal images can assist in early diagnosis and screening of retinopathy diseases. In this paper, the detection of five types of lesions and optic disc has been studied. These lesions include: Hard exudates, Soft exudates, Drusen, Microaneurysm and Hemorrhage, each of which is a sign of one or more types of disease. Our algorithm also effectively diagnoses Glaucoma and other diseases which cause changes to the optic disc. In our method, first the retina images are pre-processed. Then, our algorithm detects OD, fovea and lesions in the image and determines the type of each lesion based on Morphology. Later, the system finds the Characteristics of the Optic Disc for diagnosis of Glaucoma. It is shown that the performance of the proposed method is high. We have achieved a sensitivity of 92.5% and a specificity of 81.4%.
机译:视网膜图像中病变的自动检测可以有助于早期诊断和筛查视网膜病变疾病。 本文研究了五种类型的病变和光盘的检测。 这些病变包括:硬渗漏物,软渗出物,德鲁森,微肠溶液和出血,每种疾病是一种或多种疾病的标志。 我们的算法还有效地诊断了青光眼和其他导致视光盘变化的疾病。 在我们的方法中,首先预处理视网膜图像。 然后,我们的算法检测图像中的OD,FoVEA和病变,并根据形态确定每个病变的类型。 后来,该系统找到了光盘的特征,用于诊断青光眼。 结果表明,所提出的方法的性能很高。 我们已经实现了92.5%的敏感性,特异性为81.4%。

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