Hybrid deep learning on single wide-field optical coherence tomography scans accurately classifies glaucoma suspects

PURPOSE: Existing summary statistics based upon optical coherence tomography (OCT) scans and/or visual fields (VF) are suboptimal for distinguishing between healthy and glaucomatous eyes in the clinic. This study evaluates the extent to which a hybrid deep learning method (HDLM), combined with a sin...

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Bibliografiska uppgifter
I publikationen:J Glaucoma
Huvudupphovsmän: Muhammad, Hassan, Fuchs, Thomas J., De Cuir, Nicole, De Moraes, Carlos G, Blumberg, Dana M, Liebmann, Jeffrey M, Ritch, Robert, Hood, Donald C.
Materialtyp: Artigo
Språk:Inglês
Publicerad: 2017
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Article
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC5716847/
https://ncbi.nlm.nih.gov/pubmed/29045329
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/IJG.0000000000000765
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