Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Journal: Journal of glaucoma

Published Date: Jul 1, 2018

Abstract

PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.

Authors

Hiroki Masumoto

Department of Ophthalmology, Saneikai Tsukazaki Hospital, 68-1 Aboshi Waku, Himeji, 671-1227, Japan.
Hitoshi Tabuchi

Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.
Shunsuke Nakakura

Department of Ophthalmology, Saneikai Tsukazaki Hospital, Himeji.
Naofumi Ishitobi

Department of Ophthalmology, Tsukazaki Hospital, Himeji, Japan.
Masayuki Miki

Department of Ophthalmology, Saneikai Tsukazaki Hospital, Himeji.
Hiroki Enno

Rist Inc., Tokyo, Japan.

Keywords

Adult Aged Cross-Sectional Studies Deep Learning Female Glaucoma Humans Image Interpretation, Computer-Assisted Intraocular Pressure Male Microscopy, Confocal Middle Aged Ophthalmoscopes Reproducibility of Results Retrospective Studies Sensitivity and Specificity Severity of Illness Index Vision Disorders Visual Field Tests Visual Fields

External Resources

View on PubMed Access via DOI PubMed (29781835)

Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Abstract

Authors

Keywords

External Resources

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