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

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Vesi Yulyanti
Hanung Adi Nugroho
http://orcid.org/0000-0002-5631-1073
Igi Ardiyanto
Widhia KZ Oktoeberza

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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How to Cite
Yulyanti, V., Adi Nugroho, H., Ardiyanto, I., & Oktoeberza, W. (2019). Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection. Communications in Science and Technology, 4(1), 7-11. https://doi.org/10.21924/cst.4.1.2019.110
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Articles
Author Biographies

Vesi Yulyanti, Universitas Gadjah Mada

Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada

Hanung Adi Nugroho, Universitas Gadjah Mada

Assistant Professor

Department of Electrical Engineering and Information Technology

Igi Ardiyanto, Universitas Gadjah Mada

Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada

Widhia KZ Oktoeberza, Universitas Bengkulu

Department of Informatics, Faculty of Engineering, Universitas Bengkulu