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

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...

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Main Authors: Vesi Yulyanti, Hanung Adi Nugroho, Igi Ardiyanto, Widhia KZ Oktoeberza
Format: Article
Language:English
Published: Komunitas Ilmuwan dan Profesional Muslim Indonesia 2019-07-01
Series:Communications in Science and Technology
Subjects:
Online Access:https://cst.kipmi.or.id/index.php/cst/article/view/110
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spelling doaj-54172c23e1024af5a49acb5e63e7e4e82020-11-25T01:10:30ZengKomunitas Ilmuwan dan Profesional Muslim IndonesiaCommunications in Science and Technology2502-92582502-92662019-07-014171410.21924/cst.4.1.2019.110110Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detectionVesi Yulyanti0Hanung Adi Nugroho1Igi Ardiyanto2Widhia KZ Oktoeberza3Universitas Gadjah MadaUniversitas Gadjah MadaUniversitas Gadjah MadaUniversitas BengkuluOne 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.https://cst.kipmi.or.id/index.php/cst/article/view/110Retinal image; haemorrhages detection; dark lesions; eccentricity feature, extent feature
collection DOAJ
language English
format Article
sources DOAJ
author Vesi Yulyanti
Hanung Adi Nugroho
Igi Ardiyanto
Widhia KZ Oktoeberza
spellingShingle Vesi Yulyanti
Hanung Adi Nugroho
Igi Ardiyanto
Widhia KZ Oktoeberza
Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
Communications in Science and Technology
Retinal image; haemorrhages detection; dark lesions; eccentricity feature, extent feature
author_facet Vesi Yulyanti
Hanung Adi Nugroho
Igi Ardiyanto
Widhia KZ Oktoeberza
author_sort Vesi Yulyanti
title Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
title_short Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
title_full Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
title_fullStr Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
title_full_unstemmed Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
title_sort dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
publisher Komunitas Ilmuwan dan Profesional Muslim Indonesia
series Communications in Science and Technology
issn 2502-9258
2502-9266
publishDate 2019-07-01
description 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.
topic Retinal image; haemorrhages detection; dark lesions; eccentricity feature, extent feature
url https://cst.kipmi.or.id/index.php/cst/article/view/110
work_keys_str_mv AT vesiyulyanti darklesioneliminationbasedonareaeccentricityandextentfeaturesforsupportinghaemorrhagesdetection
AT hanungadinugroho darklesioneliminationbasedonareaeccentricityandextentfeaturesforsupportinghaemorrhagesdetection
AT igiardiyanto darklesioneliminationbasedonareaeccentricityandextentfeaturesforsupportinghaemorrhagesdetection
AT widhiakzoktoeberza darklesioneliminationbasedonareaeccentricityandextentfeaturesforsupportinghaemorrhagesdetection
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