Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis

Abstract Diabetic retinopathy (DR) is an important retinal disease threatening people with the long diabetic history. Blood leakage in retina leads to the formation of red lesions in retina the analysis of which is helpful in the determination of severity of disease. In this paper, a novel red-lesio...

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Autores principales:	Maryam Monemian, Hossein Rabbani
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7f1d2ca22b2d43118b5921e40f146718
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spelling	oai:doaj.org-article:7f1d2ca22b2d43118b5921e40f1467182021-12-02T18:02:15ZRed-lesion extraction in retinal fundus images by directional intensity changes’ analysis10.1038/s41598-021-97649-x2045-2322https://doaj.org/article/7f1d2ca22b2d43118b5921e40f1467182021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97649-xhttps://doaj.org/toc/2045-2322Abstract Diabetic retinopathy (DR) is an important retinal disease threatening people with the long diabetic history. Blood leakage in retina leads to the formation of red lesions in retina the analysis of which is helpful in the determination of severity of disease. In this paper, a novel red-lesion extraction method is proposed. The new method firstly determines the boundary pixels of blood vessel and red lesions. Then, it determines the distinguishing features of boundary pixels of red-lesions to discriminate them from other boundary pixels. The main point utilized here is that a red lesion can be observed as significant intensity changes in almost all directions in the fundus image. This can be feasible through considering special neighborhood windows around the extracted boundary pixels. The performance of the proposed method has been evaluated for three different datasets including Diaretdb0, Diaretdb1 and Kaggle datasets. It is shown that the method is capable of providing the values of 0.87 and 0.88 for sensitivity and specificity of Diaretdb1, 0.89 and 0.9 for sensitivity and specificity of Diaretdb0, 0.82 and 0.9 for sensitivity and specificity of Kaggle. Also, the proposed method has a time-efficient performance in the red-lesion extraction process.Maryam MonemianHossein RabbaniNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maryam Monemian Hossein Rabbani Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
description	Abstract Diabetic retinopathy (DR) is an important retinal disease threatening people with the long diabetic history. Blood leakage in retina leads to the formation of red lesions in retina the analysis of which is helpful in the determination of severity of disease. In this paper, a novel red-lesion extraction method is proposed. The new method firstly determines the boundary pixels of blood vessel and red lesions. Then, it determines the distinguishing features of boundary pixels of red-lesions to discriminate them from other boundary pixels. The main point utilized here is that a red lesion can be observed as significant intensity changes in almost all directions in the fundus image. This can be feasible through considering special neighborhood windows around the extracted boundary pixels. The performance of the proposed method has been evaluated for three different datasets including Diaretdb0, Diaretdb1 and Kaggle datasets. It is shown that the method is capable of providing the values of 0.87 and 0.88 for sensitivity and specificity of Diaretdb1, 0.89 and 0.9 for sensitivity and specificity of Diaretdb0, 0.82 and 0.9 for sensitivity and specificity of Kaggle. Also, the proposed method has a time-efficient performance in the red-lesion extraction process.
format	article
author	Maryam Monemian Hossein Rabbani
author_facet	Maryam Monemian Hossein Rabbani
author_sort	Maryam Monemian
title	Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
title_short	Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
title_full	Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
title_fullStr	Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
title_full_unstemmed	Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
title_sort	red-lesion extraction in retinal fundus images by directional intensity changes’ analysis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7f1d2ca22b2d43118b5921e40f146718
work_keys_str_mv	AT maryammonemian redlesionextractioninretinalfundusimagesbydirectionalintensitychangesanalysis AT hosseinrabbani redlesionextractioninretinalfundusimagesbydirectionalintensitychangesanalysis
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Red-lesion extraction in retinal fundus images by directional intensity changes’ analysis

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