Blood vessels segmentation based on three retinal images datasets

Retinal images are routinely acquired and retinal blood vessels are segmented to provide diagnostic evidence of diabetic retinopathy. Due to the acquisition process, usually these images are non-uniformly illuminated and demonstate local lu minosity and contrast variability. Based on four image pro...

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Main Authors:	Bilal, Sara Mohammed Osman Saleh, Munir, Fatin, Karbasi, Mostafa
Format:	Article
Language:	English English
Published:	Asian Research Publishing Network (ARPN) 2016
Subjects:	TA329 Engineering mathematics. Engineering analysis TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/46567/ http://irep.iium.edu.my/46567/ http://irep.iium.edu.my/46567/4/Blood_vessels.pdf http://irep.iium.edu.my/46567/7/46567_Blood%20vessels_scopus.pdf

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recordtype	eprints
spelling	iium-465672017-04-04T06:56:06Z http://irep.iium.edu.my/46567/ Blood vessels segmentation based on three retinal images datasets Bilal, Sara Mohammed Osman Saleh Munir, Fatin Karbasi, Mostafa TA329 Engineering mathematics. Engineering analysis TK7885 Computer engineering Retinal images are routinely acquired and retinal blood vessels are segmented to provide diagnostic evidence of diabetic retinopathy. Due to the acquisition process, usually these images are non-uniformly illuminated and demonstate local lu minosity and contrast variability. Based on four image processing techniques, namely, Matched filter, Hough transform, Morphological operations and Watershed, the retinal blood vessels have been segmented. Then, their strengths and weaknesses are mathematically compared in terms of retinal images segmentation. Each algorithm performance was tested on DRIVE, DRIONS and High-Resolution Fundus images database. The results show that measuring the automatic segmentation algorithm performance is based mainly on how the retinal images are acquired as well as the image processing technique used for segmentation. Neural Network has been used to recognize the retinal images. The obtained results could help the eye specialists to visually examine the retinal images. Asian Research Publishing Network (ARPN) 2016-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/46567/4/Blood_vessels.pdf application/pdf en http://irep.iium.edu.my/46567/7/46567_Blood%20vessels_scopus.pdf Bilal, Sara Mohammed Osman Saleh and Munir, Fatin and Karbasi, Mostafa (2016) Blood vessels segmentation based on three retinal images datasets. ARPN Journal of Engineering and Applied Sciences, 11 (1). pp. 387-395. ISSN 1819-6608 http://www.arpnjournals.com/jeas/volume_01_2016.htm
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TA329 Engineering mathematics. Engineering analysis TK7885 Computer engineering
spellingShingle	TA329 Engineering mathematics. Engineering analysis TK7885 Computer engineering Bilal, Sara Mohammed Osman Saleh Munir, Fatin Karbasi, Mostafa Blood vessels segmentation based on three retinal images datasets
description	Retinal images are routinely acquired and retinal blood vessels are segmented to provide diagnostic evidence of diabetic retinopathy. Due to the acquisition process, usually these images are non-uniformly illuminated and demonstate local lu minosity and contrast variability. Based on four image processing techniques, namely, Matched filter, Hough transform, Morphological operations and Watershed, the retinal blood vessels have been segmented. Then, their strengths and weaknesses are mathematically compared in terms of retinal images segmentation. Each algorithm performance was tested on DRIVE, DRIONS and High-Resolution Fundus images database. The results show that measuring the automatic segmentation algorithm performance is based mainly on how the retinal images are acquired as well as the image processing technique used for segmentation. Neural Network has been used to recognize the retinal images. The obtained results could help the eye specialists to visually examine the retinal images.
format	Article
author	Bilal, Sara Mohammed Osman Saleh Munir, Fatin Karbasi, Mostafa
author_facet	Bilal, Sara Mohammed Osman Saleh Munir, Fatin Karbasi, Mostafa
author_sort	Bilal, Sara Mohammed Osman Saleh
title	Blood vessels segmentation based on three retinal images datasets
title_short	Blood vessels segmentation based on three retinal images datasets
title_full	Blood vessels segmentation based on three retinal images datasets
title_fullStr	Blood vessels segmentation based on three retinal images datasets
title_full_unstemmed	Blood vessels segmentation based on three retinal images datasets
title_sort	blood vessels segmentation based on three retinal images datasets
publisher	Asian Research Publishing Network (ARPN)
publishDate	2016
url	http://irep.iium.edu.my/46567/ http://irep.iium.edu.my/46567/ http://irep.iium.edu.my/46567/4/Blood_vessels.pdf http://irep.iium.edu.my/46567/7/46567_Blood%20vessels_scopus.pdf
first_indexed	2023-09-18T21:06:18Z
last_indexed	2023-09-18T21:06:18Z
_version_	1777410955741757440

Blood vessels segmentation based on three retinal images datasets

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