基于机器学习的眼底图像渗出物提取

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引用次数: 1

摘要

糖尿病患者因此不得不忍受其他几种疾病。糖尿病视网膜病变就是其中一种影响糖尿病患者的疾病。如果不及时治疗,这种疾病会影响患者的眼睛,导致永久性失明。另一种疾病是渗出,其中脂质残留物从受损的毛细血管中泄漏出来。它看起来像黄色的斑点。硬渗出物会导致危及生命的疾病。检测硬渗出物有助于眼科医生诊断患者病情的严重程度,从而有助于更好地用药。本文提出了一种调整图像对比度的方法,从而有助于检测硬渗出物,为进一步处理提供依据。在这项工作中,首先应用了Otsu算法,然后由于Otsu算法的缺点与机器学习技术进行了比较。
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Exudate Extraction from Fundus Images using Machine Learning
Patients suffering from diabetes have to bear several other disorders due to this. Diabetic Retinopathy is one such disorder which affects diabetic patients. This disorder affects the patient’s eye leading to permanent blindness if left untreated. Another disorder is exudates in which lipid residues leak out from damaged capillaries. It appears as yellow flecks. Hard exudates can lead to life threatening disorders. Detecting Hard exudates help the Ophthalmologist to diagnose the severity of the patient’s condition and in turn help in better medication. This paper presents a method to adjust the contrast of the image which in turn helps in detecting the hard exudates which can be used for further processing. In this work, initially Otsu algorithm is applied and then compared with Machine Learning techniques due to the disadvantage of Otsu.
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