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Automatic Exudate Detection Using Eye Fundus Image Analysis Due to Diabetic Retinopathy

机译:使用糖尿病性视网膜病变的眼底图像分析自动进行渗出液检测

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Diabetic retinopathy (damage to the retina) is a disease caused by complications of diabetes, which can eventually lead to blindness. It is an ocular manifestation of diabetes, a systemic disease, which affects up to 80 percent of all patients who have had diabetes for 10 years or more. Despite these intimidating statistics, research indicates that at least 90% of these new cases could be reduced if there was proper and vigilant treatment and monitoring of the patient eyes. The longer a person has diabetes, the higher his or her chances of developing diabetic retinopathy. In this paper, we introduced a new method for eye fundus image analysis, based on exudate segmentation. The proposed algorithm detects the existence of exudates and measures its distribution. In this paper, we classified images of eye fundus into no-exudate or have exudates. This initial classification helps physicians to initiate a treatment process for infected patients. The algorithm is tested using DIARETDBO. The results proved the reliability and robustness of algorithm.
机译:糖尿病性视网膜病(对视网膜的损害)是由糖尿病并发症引起的疾病,最终可能导致失明。它是糖尿病的一种眼部表现,是一种全身性疾病,影响了10年以上糖尿病患者的80%。尽管有这些令人生畏的统计数据,但研究表明,如果进行适当和警惕的治疗并监测患者的眼睛,至少可以减少90%的新病例。一个人患有糖尿病的时间越长,患糖尿病性视网膜病的机会就越高。在本文中,我们介绍了一种基于渗出液分割的眼底图像分析新方法。所提出的算法检测渗出液的存在并测量其分布。在本文中,我们将眼底图像分为无渗出液或有渗出液。此初始分类可帮助医生启动针对感染患者的治疗过程。使用DIARETDBO测试该算法。结果证明了算法的可靠性和鲁棒性。

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