Automatic feature learning for glaucoma detection based on deep learning

Xiangyu Chen, Yanwu Xu, Shuicheng Yan, Damon Wing Kee Wong, Tien Yin Wong, Jiang Liu

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

103 Citations (Scopus)

Abstract

Glaucoma is a chronic and irreversible eye disease in which the optic nerve is progressively damaged, leading to deterioration in vision and quality of life. In this paper, we present an Automatic feature Learning for glAucomaDetection based onDeep LearnINg (ALADDIN),with deep convolutional neural network (CNN) for feature learning. Different from the traditional convolutional layer that uses linear filters followed by a nonlinear activation function to scan the input, the adopted network embeds micro neural networks (multilayer perceptron) with more complex structures to abstract the data within the receptive field. Moreover, a contextualizing deep learning structure is proposed in order to obtain a hierarchical representation of fundus images to discriminate between glaucoma and non-glaucoma pattern,where the network takes the outputs fromother CNN as the context information to boost the performance. Extensive experiments are performed on the ORIGA and SCES datasets. The results showarea under curve (AUC) of the receiver operating characteristic curve in glaucoma detection at 0.838 and 0.898 in the two databases,much better than state-of-the-art algorithms. The method could be used for glaucoma diagnosis.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2015 - 18th International Conference, Proceedings
EditorsAlejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells
PublisherSpringer Verlag
Pages669-677
Number of pages9
ISBN (Print)9783319245737
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: 5 Oct 20159 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9351
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Country/TerritoryGermany
CityMunich
Period5/10/159/10/15

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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