NDLI: A new tool to connect blood vessels in fundus retinal images

Content Provider	IEEE Xplore Digital Library
Author	Caliva, F. Aletti, M. Al-Diri, B. Hunter, A.
Copyright Year	2015
Description	Author affiliation: Inria Paris-Rocquencourt, Univ. Paris 6, Paris, France (Aletti, M.) \|\| Univ. of Lincoln, Lincoln, UK (Hunter, A.) \|\| Dept. of Comput. Sci., Univ. of Lincoln, Lincoln, UK (Caliva, F.; Al-Diri, B.)
Abstract	This paper presents a novel tool that allows a user to reconstruct the retinal vascular network from fundus images. The retinal vasculature consists of trees of arteries and veins. Common segmentation algorithms are not able to completely segment out the blood vessels in fundus images. This failure results in a set of disconnected or broken up vascular segments. Reconstructing the whole network has crucial importance because it can offer insight into global features not considered so far, including retinal fluid dynamics. This tool uses implicit neural cost functions to join vessel segments. Results have shown that the quality of the segmentation affects the outcome of connectivity algorithms and by enhancing the segmentation the connectivity can be improved.
Starting Page	4343
Ending Page	4346
File Size	2900609
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7319356
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Retina Biomedical imaging Junctions Blood vessels Feature extraction Bifurcation retinal trees vessels connectivity junction resolution connectivity tool
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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