Retinal artery and vein classification via dominant sets clustering-based vascular topology estimation

Yitian Zhao*, Jianyang Xie, Pan Su, Yalin Zheng, Yonghuai Liu, Jun Cheng, Jiang Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

32 Citations (SciVal)

Abstract

The classification of the retinal vascular tree into arteries and veins is important in understanding the relation between vascular changes and a wide spectrum of diseases. In this paper, we have proposed a novel framework that is capable of making the artery/vein (A/V) distinction in retinal color fundus images. We have successfully adapted the concept of dominant sets clustering and formalize the retinal vessel topology estimation and the A/V classification problem as a pairwise clustering problem. Dominant sets clustering is a graph-theoretic approach that has been proven to work well in data clustering. The proposed approach has been applied to three public databases (INSPIRE, DRIVE and VICAVR) and achieved high accuracies of 91.0%, 91.2%, and 91.0%, respectively. Furthermore, we have made manual annotations of vessel topologies from these databases, and this annotation will be released for public access to facilitate other researchers in the community to do research in the same and related topics.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention – MICCAI 2018
EditorsAlejandro F. Frangi, Gabor Fichtinger, Christos Davatzikos, Carlos Alberola-López, Julia A. Schnabel
PublisherSpringer Nature
Pages56-64
Number of pages9
ISBN (Print)9783030009335
DOIs
Publication statusPublished - 01 Jan 2018
Event21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: 16 Sept 201820 Sept 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11071 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
Country/TerritorySpain
CityGranada
Period16 Sept 201820 Sept 2018

Keywords

  • Artery/vein classification
  • Dominant sets
  • Topology
  • Vessel

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