An Automated Blood Vessel Segmentation Algorithm Using Histogram Equalization and Automatic Threshold Selection

This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhance...

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Bibliographic Details
Published in:Journal of digital imaging Vol. 24; no. 4; pp. 564 - 572
Main Authors: Saleh, Marwan D., Eswaran, C., Mueen, Ahmed
Format: Journal Article
Language:English
Published: New York Springer-Verlag 01.08.2011
Subjects:
Algorithms
Databases, Factual
Diabetic Retinopathy - diagnosis
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Imaging
Medicine
Medicine & Public Health
Pattern Recognition, Automated - methods
Photography
Radiology
Reproducibility of Results
Retinal Vessels - anatomy & histology
Diabetic retinopathy
automatic thresholding
histogram equalization
blood vessel segmentation
ISSN:0897-1889, 1618-727X, 1618-727X
Online Access:Get full text
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Summary:This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhancement and thresholding offers an automated segmentation procedure for retinal blood vessels. To evaluate the performance of the new algorithm, experiments are conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm performs better than the other known algorithms in terms of accuracy. Furthermore, the proposed algorithm being simple and easy to implement, is best suited for fast processing applications.
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ISSN:0897-1889
1618-727X
1618-727X
DOI:10.1007/s10278-010-9302-9