A deep learning approach to automatic detection of early glaucoma from visual fields.

Journal: PloS one

Published Date: Nov 28, 2018

Abstract

PURPOSE: To investigate the suitability of multi-scale spatial information in 30o visual fields (VF), computed from a Convolutional Neural Network (CNN) classifier, for early-glaucoma vs. control discrimination.

Authors

Şerife Seda Kucur

ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
Gábor Holló

Department of Ophthalmology, Semmelweis University, Budapest, Hungary.
Raphael Sznitman

ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.

Keywords

Algorithms Databases as Topic Deep Learning Early Diagnosis Glaucoma Humans Image Processing, Computer-Assisted Neural Networks, Computer Visual Fields

External Resources

View on PubMed Access via DOI PubMed (30485270)

A deep learning approach to automatic detection of early glaucoma from visual fields.

Abstract

Authors

Keywords

External Resources

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