Optic cup segmentation for glaucoma detection using low-rank superpixel representation

Yanwu Xu, Lixin Duan, Stephen Lin, Xiangyu Chen, Damon Wing Kee Wong, Tien Yin Wong, Jiang Liu

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

53 Citations (Scopus)

Abstract

We present an unsupervised approach to segment optic cups in fundus images for glaucoma detection without using any additional training images. Our approach follows the superpixel framework and domain prior recently proposed in [1], where the superpixel classification task is formulated as a low-rank representation (LRR) problem with an efficient closed-form solution. Moreover, we also develop an adaptive strategy for automatically choosing the only parameter in LRR and obtaining the final result for each image. Evaluated on the popular ORIGA dataset, the results show that our approach achieves better performance compared with existing techniques.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
PublisherSpringer Verlag
Pages788-795
Number of pages8
EditionPART 1
ISBN (Print)9783319104034
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States
Duration: 14 Sep 201418 Sep 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8673 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
Country/TerritoryUnited States
CityBoston, MA
Period14/09/1418/09/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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