Efficient optic cup detection from intra-image learning with retinal structure priors

Yanwu Xu, Jiang Liu, Stephen Lin, Dong Xu, Carol Y. Cheung, Tin Aung, Tien Yin Wong

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

14 Citations (Scopus)

Abstract

We present a superpixel based learning framework based on retinal structure priors for glaucoma diagnosis. In digital fundus photographs, our method automatically localizes the optic cup, which is the primary image component clinically used for identifying glaucoma. This method provides three major contributions. First, it proposes processing of the fundus images at the superpixel level, which leads to features more descriptive and effective than those employed by pixel-based techniques, while yielding significant computational savings over methods based on sliding windows. Second, the classifier learning process does not rely on pre-labeled training samples, but rather the training samples are extracted from the test image itself using structural priors on relative cup and disc positions. Third, we present a classification refinement scheme that utilizes both structural priors and local context. Tested on the ORIGA−light clinical dataset comprised of 650 images, the proposed method achieves a 26.7% non-overlap ratio with manually-labeled ground-truth and a 0.081 absolute cup-to-disc ratio (CDR) error, a simple yet widely used diagnostic measure. This level of accuracy is comparable to or higher than the state-of-the-art technique [1], with a speedup factor of tens or hundreds.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
EditorsNicholas Ayache, Herve Delingette, Polina Golland, Kensaku Mori
PublisherSpringer Verlag
Pages58-65
Number of pages8
ISBN (Print)9783642334146
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 - Nice, France
Duration: 1 Oct 20125 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7510 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
Country/TerritoryFrance
CityNice
Period1/10/125/10/12

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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