糖尿病视网膜病变的诊断:一种迁移学习方法

Farhan Nabil Mohd Noor, A. P. Majeed, Mohd Azraai Mod Razmam, I. M. Khairuddin, W. M. Isa
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引用次数: 1

摘要

糖尿病视网膜病变是发生在眼部的糖尿病并发症之一。它会损害血管,导致血液和其他液体因血糖水平升高而泄漏。糖尿病视网膜病变是一种悄无声息的疾病,直到视网膜异常发展到难以或无法用药时,患者才会发现。它还可能导致患者完全失明。然而,自动筛检机可以帮助眼科医生尽快诊断糖尿病视网膜病变患者,从而克服这个问题。因此,本研究通过使用迁移学习模型(如VGG16)提取特征并将其提供给支持向量机(SVM), k-近邻(kNN)和随机森林(RF)进行分类,来研究自动筛选机的有效性。结果表明,VGG16-SVM流水线在糖尿病视网膜病变的分类中表现出最理想的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Diagnosis of Diabetic Retinopathy: A Transfer Learning Approach
Diabetic Retinopathy is one of the complications of diabetes mellitus that occurs to the eye. It damages the blood vessels, which cause the leaking of the blood and other fluids due to the elevated blood glucose level. Diabetic Retinopathy is a quiet ailment that patients may not discover until abnormalities in the retina have progressed to the point that medication is difficult or impossible. It can also result in patients losing their sight completely. However, an automated screening machine may help overcome this problem by helping the ophthalmologist diagnose diabetic retinopathy patients as soon as possible. Hence, this research investigates the effectiveness of automatic screening machine by employing the Transfer Learning model such as VGG16 to extract the features and fed them to the Support Vector Machine (SVM), k-Nearest Neighbour (kNN) and Random Forest (RF) for the classification. It was shown that the VGG16-SVM pipeline displayed the most promising performance on the classification of Diabetic Retinopathy.
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