Title
Improving retinal artery and vein classification by means of a minimal path approach
Abstract
This paper describes a technique for the retinal vessel classification into artery and vein categories from fundus images within a framework to compute the arteriovenous ratio. This measure is used to assess the patient condition, mainly in hypertension and it is computed as the ratio between artery and vein widths. To this end, the vessels are segmented and measured in several circumferences concentric to the optic nerve. The resulting vessel segments at each radius are classified as artery or vein independently. After that, a tracking procedure joins vessel segments in different radii that belong to the same vessel. Finally, a voting system is applied to obtain the final class of the whole vessel. The methodology has been tested in a data set of 100 images labeled manually by two medical experts and a classification rate of over 87.68 % has been obtained.
Year
DOI
Venue
2013
10.1007/s00138-012-0442-4
Mach. Vis. Appl.
Keywords
Field
DocType
Retinal vessel classification,Arteries,Veins,Minimal path,Arteriovenous ratio
Artery,Concentric,Pattern recognition,Computer science,Retinal Artery,Vein,Fundus (eye),Artificial intelligence,Classification rate,Optic nerve
Journal
Volume
Issue
ISSN
24
5
0932-8092
Citations 
PageRank 
References 
17
0.77
13
Authors
9
Name
Order
Citations
PageRank
S. G. Vázquez1404.56
Brais Cancela2669.19
Noelia Barreira318217.47
Manuel G. Penedo428424.93
M. Rodríguez-Blanco5171.11
M. Pena Seijo6170.77
G. Coll Tuero7170.77
M. A. Barceló8170.77
M. Saez9170.77