Skip to main content
Journal cover image

Automatic feature learning for glaucoma detection based on deep learning

Publication ,  Conference
Chen, X; Xu, Y; Yan, S; Wong, DWK; Wong, TY; Liu, J
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2015

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.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319245737

Publication Date

January 1, 2015

Volume

9351

Start / End Page

669 / 677

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Chen, X., Xu, Y., Yan, S., Wong, D. W. K., Wong, T. Y., & Liu, J. (2015). Automatic feature learning for glaucoma detection based on deep learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9351, pp. 669–677). https://doi.org/10.1007/978-3-319-24574-4_80
Chen, X., Y. Xu, S. Yan, D. W. K. Wong, T. Y. Wong, and J. Liu. “Automatic feature learning for glaucoma detection based on deep learning.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9351:669–77, 2015. https://doi.org/10.1007/978-3-319-24574-4_80.
Chen X, Xu Y, Yan S, Wong DWK, Wong TY, Liu J. Automatic feature learning for glaucoma detection based on deep learning. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2015. p. 669–77.
Chen, X., et al. “Automatic feature learning for glaucoma detection based on deep learning.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9351, 2015, pp. 669–77. Scopus, doi:10.1007/978-3-319-24574-4_80.
Chen X, Xu Y, Yan S, Wong DWK, Wong TY, Liu J. Automatic feature learning for glaucoma detection based on deep learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2015. p. 669–677.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783319245737

Publication Date

January 1, 2015

Volume

9351

Start / End Page

669 / 677

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences