Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection

Vesi Yulyanti, Hanung Adi Nugroho, I. Ardiyanto, Widhia K.Z. Oktoeberza
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Abstract

One of the complications due to the long-term of diabetes is retinal vessels damaging called diabetic retinopathy. It is characterised by appearing the bleeding spots in the large size (haemorrhages) on the surface of retina. Early detection of haemorrhages is needed for preventing the worst effect which leads to vision loss. This study aims to detect haemorrhages by eliminating other dark lesion objects that have similar characteristics with haemorrhages based on three features, i.e. area, eccentricity and extent features. This study uses 43 retinal fundus images taken from DIARETDB1 database. Based on the validation process, the average level of sensitivity gained is 80.5%. These results indicate that the proposed method is quite capable of detecting haemorrhages which appear in the retinal surface.
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基于面积、偏心率和范围特征的深色病灶消除,支持出血检测
长期糖尿病的并发症之一是视网膜血管损伤,称为糖尿病视网膜病变。其特征是在视网膜表面出现大面积出血点(出血)。需要及早发现出血,以防止导致视力下降的最坏影响。本研究旨在根据三个特征,即面积、偏心率和范围特征,通过消除与出血具有相似特征的其他深色病变对象来检测出血。本研究使用了从DIARETDB1数据库中获取的43张视网膜眼底图像。根据验证过程,获得的平均灵敏度为80.5%。这些结果表明,所提出的方法非常能够检测视网膜表面出现的出血。
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来源期刊
Communications in Science and Technology
Communications in Science and Technology Engineering-Engineering (all)
CiteScore
3.20
自引率
0.00%
发文量
13
审稿时长
24 weeks
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