Superpixel classification based optic disc segmentation

Jun Cheng, Jiang Liu, Yanwu Xu, Fengshou Yin, Damon Wing Kee Wong, Ngan Meng Tan, Ching Yu Cheng, Yih Chung Tham, Tien Yin Wong

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

7 Citations (Scopus)


Optic disc segmentation in retinal fundus images is important in computer aided diagnosis. In this paper, an optic disc segmentation method based on superpixel classification is proposed. In the classification, histograms from contrast enhanced image channels and center surround statistics from center surround difference maps are proposed as features to determine each superpixel as disc or non disc. In the training step, bootstrapping is adopted to handle the unbalanced cluster issue due to the presence of peripapillary atrophy. A self-assessment reliability score is computed to evaluate the quality of the automated optic disc segmentation. The proposed method has been tested on a database of 650 images with optic disc boundaries marked by trained professionals manually. The experimental results show a mean overlapping error of 9.5%, better than previous methods. The results also show an increase in overlapping error as the reliability score is reduced, which justifies the effectiveness of the self-assessment. The method can be used in computer aided diagnosis systems and the self-assessment can be used as an indicator of results with large errors and thus enhance the clinical deployment of the automatic segmentation.

Original languageEnglish
Title of host publicationComputer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
Number of pages12
EditionPART 2
Publication statusPublished - 2013
Externally publishedYes
Event11th Asian Conference on Computer Vision, ACCV 2012 - Daejeon, Korea, Republic of
Duration: 5 Nov 20129 Nov 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7725 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th Asian Conference on Computer Vision, ACCV 2012
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)


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