Retinal Blood Vessel Segmentation Approach Based on Mathematical Morphology

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86099400" target="_blank" >RIV/61989100:27240/15:86099400 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S1877050915028355?via%3Dihub" target="_blank" >http://www.sciencedirect.com/science/article/pii/S1877050915028355?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.procs.2015.09.005" target="_blank" >10.1016/j.procs.2015.09.005</a>

Result language
angličtina
Original language name
Retinal Blood Vessel Segmentation Approach Based on Mathematical Morphology
Original language description
Diabetic retinopathy is a disease, which forms a severe threat on sight. It may reach to blindness among working age people. By analyzing and detecting of vasculature structures in retinal images, we can early detect the diabetes in advanced stages by comparison of its states of retinal blood vessels. In this paper, we present blood vessel segmentation approach, which can be used in computer based retinal image analysis to extract the retinal image vessels. Mathematical morphology and K-means clustering are used to segment the vessels. To enhance the blood vessels and suppress the background information, we perform smoothing operation on the retinal image using mathematical morphology. Then the enhanced image is segmented using K-means clustering algorithm. The proposed approach is tested on the DRIVE dataset and is compared with alternative approaches. Experimental results obtained by the proposed approach showed that it is effective as it achieved average accuracy of 95.10% and best accuracy of 96.25%. (C) 2015 The Authors.
Czech name
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Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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