Blood vessels segmentation based on three retinal images datasets

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

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Abstract

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.

Item Type:	Article (Journal)
Additional Information:	6951/46567
Uncontrolled Keywords:	Retinal images, Eye blood vessels, Segmentation, Database, Neural Network
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA329 Engineering mathematics. Engineering analysis T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering Kulliyyah of Engineering > Department of Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Sara Bilal
Date Deposited:	10 Feb 2016 14:50
Last Modified:	04 Apr 2017 14:56
URI:	http://irep.iium.edu.my/id/eprint/46567

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