Incorporating privileged genetic information for fundus image based glaucoma detection.

Journal Article

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.

Duke Authors

Cited Authors

  • Duan, L; Xu, Y; Li, W; Chen, L; Wing, DWK; Wong, TY; Liu, J

Published Date

  • January 2014

Published In

  • Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

Volume / Issue

  • 17 / Pt 2

Start / End Page

  • 204 - 211

PubMed ID

  • 25485380

Language

  • eng