Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks

Vinayak S Joshi; Joseph M Reinhardt; Mona K Garvin; Michael D Abramoff

doi:10.1371/journal.pone.0088061

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Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks

Journal article

Open access

Peer reviewed

Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks

Vinayak S Joshi, Joseph M Reinhardt, Mona K Garvin and Michael D Abramoff

PloS one, Vol.9(2), e88061

2014

DOI: 10.1371/journal.pone.0088061

PMCID: PMC3922768

PMID: 24533066

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Abstract

The separation of the retinal vessel network into distinct arterial and venous vessel trees is of high interest. We propose an automated method for identification and separation of retinal vessel trees in a retinal color image by converting a vessel segmentation image into a vessel segment map and identifying the individual vessel trees by graph search. Orientation, width, and intensity of each vessel segment are utilized to find the optimal graph of vessel segments. The separated vessel trees are labeled as primary vessel or branches. We utilize the separated vessel trees for arterial-venous (AV) classification, based on the color properties of the vessels in each tree graph. We applied our approach to a dataset of 50 fundus images from 50 subjects. The proposed method resulted in an accuracy of 91.44% correctly classified vessel pixels as either artery or vein. The accuracy of correctly classified major vessel segments was 96.42%.

Algorithms

Automation

Fuzzy logic

Reproducibility of Results

Humans

Color

Image Processing, Computer-Assisted - methods

Retinal Vein - physiology

Retina - physiology

Retinal Artery - physiology

Pattern Recognition, Automated

Fundus Oculi

Cluster Analysis

Databases, Factual

Details

Title: Subtitle: Automated method for identification and artery-venous classification of vessel trees in retinal vessel networks
Creators: Vinayak S Joshi - Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States of America
Joseph M Reinhardt - Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, United States of America
Mona K Garvin - University of Iowa
Michael D Abramoff - University of Iowa, The University of Iowa Institute for Vision Research
Resource Type: Journal article
Publication Details: PloS one, Vol.9(2), e88061
DOI: 10.1371/journal.pone.0088061
PMID: 24533066
PMCID: PMC3922768
NLM abbreviation: PLoS One
ISSN: 1932-6203
eISSN: 1932-6203
Publisher: United States
Grant note: R01 EY017066 / NEI NIH HHS
Language: English
Date published: 2014
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Ophthalmology and Visual Sciences
Record Identifier: 9983806387802771

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