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Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.

Purpose: Retinal blood vessel segmentation is crucial as it is the earliest process in measuring various indicators of retinopathy sign such as arterial-venous nicking, and focal arteriolar and generalized arteriolar narrowing. The segmentation can be clinically used if its accuracy is close to 100%...

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Main Authors: Kipli, Kuryati, Jiris, Cripen, Sahari, Siti Kudnie, Sapawi, Rohana, Junaidi, Nazreen, Sapawi, Marini, Hong Ping, Kismet, Zulcaffle, Tengku Mohd Affendi
Format: Conference or Workshop Item
Language:English
Published: 2017
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://ir.unimas.my/id/eprint/19085/1/Retinal%20Image%20Segmentation%20Kuryati%20USJC_Formatted%20-%20%28abstrak%29.pdf
http://ir.unimas.my/id/eprint/19085/
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spelling my.unimas.ir.190852017-12-29T06:45:31Z http://ir.unimas.my/id/eprint/19085/ Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy. Kipli, Kuryati Jiris, Cripen Sahari, Siti Kudnie Sapawi, Rohana Junaidi, Nazreen Sapawi, Marini Hong Ping, Kismet Zulcaffle, Tengku Mohd Affendi QA75 Electronic computers. Computer science Purpose: Retinal blood vessel segmentation is crucial as it is the earliest process in measuring various indicators of retinopathy sign such as arterial-venous nicking, and focal arteriolar and generalized arteriolar narrowing. The segmentation can be clinically used if its accuracy is close to 100%. In this study, a new method of segmentation is developed for extraction of retinal blood vessel. Methods: In this paper, we present a new automated method to extract blood vessels in retinal fundus images. The proposed method comprises of two main parts and a few subcomponents which include pre-processing and segmentation. The main focus for the segmentation part is two morphological reconstructions which are the morphological reconstructions followed by the morphological top-hat transform. Then the technique to classify the vessel pixels and background pixels is Otsu’s thresholding. The image database used in this study is the High Resolution Fundus Image Database (HRFID). Results: The developed segmentation method accuracy are 95.17%, 92.06% and 94.71% when tested on dataset of healthy, diabetic retinopathy (DR) and glaucoma patients respectively. Conclusion: Overall, the performance of the proposed method is comparable with existing methods with overall accuracies were more than 90 % for all three different categories: healthy, DR and glaucoma 2017-10-20 Conference or Workshop Item PeerReviewed text en http://ir.unimas.my/id/eprint/19085/1/Retinal%20Image%20Segmentation%20Kuryati%20USJC_Formatted%20-%20%28abstrak%29.pdf Kipli, Kuryati and Jiris, Cripen and Sahari, Siti Kudnie and Sapawi, Rohana and Junaidi, Nazreen and Sapawi, Marini and Hong Ping, Kismet and Zulcaffle, Tengku Mohd Affendi (2017) Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy. In: UNIMAS SILVER JUBILEE CONFERENCE 2017 (USJC 2017), 18-20 October 2017, Pullman Kuching.
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Kipli, Kuryati
Jiris, Cripen
Sahari, Siti Kudnie
Sapawi, Rohana
Junaidi, Nazreen
Sapawi, Marini
Hong Ping, Kismet
Zulcaffle, Tengku Mohd Affendi
Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.
description Purpose: Retinal blood vessel segmentation is crucial as it is the earliest process in measuring various indicators of retinopathy sign such as arterial-venous nicking, and focal arteriolar and generalized arteriolar narrowing. The segmentation can be clinically used if its accuracy is close to 100%. In this study, a new method of segmentation is developed for extraction of retinal blood vessel. Methods: In this paper, we present a new automated method to extract blood vessels in retinal fundus images. The proposed method comprises of two main parts and a few subcomponents which include pre-processing and segmentation. The main focus for the segmentation part is two morphological reconstructions which are the morphological reconstructions followed by the morphological top-hat transform. Then the technique to classify the vessel pixels and background pixels is Otsu’s thresholding. The image database used in this study is the High Resolution Fundus Image Database (HRFID). Results: The developed segmentation method accuracy are 95.17%, 92.06% and 94.71% when tested on dataset of healthy, diabetic retinopathy (DR) and glaucoma patients respectively. Conclusion: Overall, the performance of the proposed method is comparable with existing methods with overall accuracies were more than 90 % for all three different categories: healthy, DR and glaucoma
format Conference or Workshop Item
author Kipli, Kuryati
Jiris, Cripen
Sahari, Siti Kudnie
Sapawi, Rohana
Junaidi, Nazreen
Sapawi, Marini
Hong Ping, Kismet
Zulcaffle, Tengku Mohd Affendi
author_facet Kipli, Kuryati
Jiris, Cripen
Sahari, Siti Kudnie
Sapawi, Rohana
Junaidi, Nazreen
Sapawi, Marini
Hong Ping, Kismet
Zulcaffle, Tengku Mohd Affendi
author_sort Kipli, Kuryati
title Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.
title_short Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.
title_full Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.
title_fullStr Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.
title_full_unstemmed Morphological and Otsu Thresholding Based Retinal Blood Vessel Segmentation for Detection of Retinopathy.
title_sort morphological and otsu thresholding based retinal blood vessel segmentation for detection of retinopathy.
publishDate 2017
url http://ir.unimas.my/id/eprint/19085/1/Retinal%20Image%20Segmentation%20Kuryati%20USJC_Formatted%20-%20%28abstrak%29.pdf
http://ir.unimas.my/id/eprint/19085/
_version_ 1644512987064565760
score 13.211869

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