Computer Vision Method for Grading of Health of a Fundus Image on Basis of Presence of Red Lesions

S. Bhattacharya, J. Sehgal, Ashish Issac, M. Dutta, Radim Burget, M. Kolarík
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引用次数: 7

Abstract

Diabetic Retinopathy is one of those eye diseases which may cause permanent loss of vision if not treated at an early stage. The current paper proposes an algorithmic rule for detection of red lesions and grading the severity of a fundus image depending on its location in the image. Some significant and deciding objects like optic disc and macula are segmented using adaptive intensity-based threshold, geometrical features, k-means clustering and morphological operations. Imaging techniques like color normalization, median filtering and morphological operations are used for segmentation of blood vessels and red lesions. Finally, a region-based framework has been used for grading the severity of the disease affecting the patient. The proposed method has achieved an accuracy of 89%. The proposed method has given encouraging results and can be used in development of some devices in this field.
基于红色病灶的眼底图像健康度计算机视觉分级方法
糖尿病视网膜病变是一种如不及早治疗可能导致永久性视力丧失的眼病。本文提出了一种算法规则,用于检测红色病变,并根据其在图像中的位置对眼底图像的严重程度进行分级。使用基于自适应强度的阈值、几何特征、k-means聚类和形态学操作对视盘和黄斑等重要和决定性的物体进行分割。采用颜色归一化、中值滤波、形态学等成像技术对血管和红色病灶进行分割。最后,一个基于区域的框架被用于对影响患者的疾病的严重程度进行分级。该方法的准确率达到89%。该方法取得了令人鼓舞的结果,可用于该领域某些器件的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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