Evaluation of deep convolutional neural networks for glaucoma detection

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ID: 114756
2019
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Abstract
DCNNs may be a useful tool for detecting glaucoma or glaucoma-suspected eyes by use of fundus color images. Proper preprocessing and collection of qualified images are essential to improving the discriminative ability.
Reference Key
s2019japaneseevaluation Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Phan S;Satoh S;Yoda Y;Kashiwagi K;Oshika T; ;;
Journal japanese journal of ophthalmology
Year 2019
DOI
DOI not found
URL
https://www.pubmed.gov/30798379/
Keywords
neural networks National Center for Biotechnology Information NCBI NLM MEDLINE humans pubmed abstract nih national institutes of health national library of medicine computer* Retrospective Studies diagnostic techniques ophthalmological* roc curve pmid:30798379 doi:10.1007/s10384-019-00659-6 sang phan shin'ichi satoh japan ocular imaging registry research group glaucoma / diagnosis* optic disk / diagnostic imaging*

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