Superpixel classification based optic cup segmentation

Jun Cheng, Jiang Liu, Dacheng Tao, Fengshou Yin, Damon Wing Kee Wong, Yanwu Xu, Tien Yin Wong

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

15 Citations (Scopus)


In this paper, we propose a superpixel classification based optic cup segmentation for glaucoma detection. In the proposed method, each optic disc image is first over-segmented into superpixels. Then mean intensities, center surround statistics and the location features are extracted from each superpixel to classify it as cup or non-cup. The proposed method has been evaluated in one database of 650 images with manual optic cup boundaries marked by trained professionals and one database of 1676 images with diagnostic outcome. Experimental results show average overlapping error around 26.0% compared with manual cup region and area under curve of the receiver operating characteristic curve in glaucoma detection at 0.811 and 0.813 in the two databases, much better than other methods. The method could be used for glaucoma screening.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings
Number of pages8
EditionPART 3
Publication statusPublished - 2013
Externally publishedYes
Event16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: 22 Sept 201326 Sept 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume8151 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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