Dual-input convolutional neural network for glaucoma diagnosis using spectral-domain optical coherence tomography

• Published in: British journal of ophthalmology Vol. 105; no. 11; pp. 1555 - 1560
• Main Authors: Sun, Sukkyu, Ha, Ahnul, Kim, Young Kook, Yoo, Byeong Wook, Kim, Hee Chan, Park, Ki Ho
• Format: Journal Article
• Language: English
• Published: BMA House, Tavistock Square, London, WC1H 9JR BMJ Publishing Group Ltd 01.11.2021; BMJ Publishing Group LTD
• Subjects: Algorithms; Cardiovascular disease; Classification; Clinical science; Deep learning; Glaucoma; Glaucoma - diagnostic imaging; Glaucoma, Open-Angle - diagnostic imaging; Humans; Imaging; Intraocular Pressure; Macula; Medical diagnosis; Neural networks; Neural Networks, Computer; Optic Nerve; Optics; Retinal Ganglion Cells; ROC Curve; Tomography; Tomography, Optical Coherence; United States > US; Glaucoma; Macula; Imaging; Optic Nerve

Background/AimsTo evaluate, with spectral-domain optical coherence tomography (SD-OCT), the glaucoma-diagnostic ability of a deep-learning classifier.MethodsA total of 777 Cirrus high-definition SD-OCT image sets of the retinal nerve fibre layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL)...