Incorporating privileged genetic information for fundus image based glaucoma detection

Lixin Duan, Yanwu Xu, Wen Li, Lin Chen, Damon Kee Wing, Tien Wong, Jiang Liu

Research output: Journal PublicationArticlepeer-review

4 Citations (Scopus)


Visual features extracted from retinal fundus images have been increasingly used for glaucoma detection, as those images are generally easy to acquire. In recent years, genetic researchers have found that some single nucleic polymorphisms (SNPs) play important roles in the manifestation of glaucoma and also show superiority over fundus images for glaucoma detection. In this work, we propose to use the SNPs to form the so-called privileged information and deal with a practical problem where both fundus images and privileged genetic information exist for the training subjects, while the test objects only have fundus images. To solve this problem, we present an effective approach based on the learning using privileged information (LUPI) paradigm to train a predictive model for the image visual features. Extensive experiments demonstrate the usefulness of our approach in incorporating genetic information for fundus image based glaucoma detection.

Original languageEnglish
Pages (from-to)204-211
Number of pages8
JournalMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Publication statusPublished - 2014
Externally publishedYes

ASJC Scopus subject areas

  • General Medicine


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