Park Keunheung

The Relationship Between Bruch's Membrane Opening-Minimum Rim Width and Retinal Nerve Fiber Layer Thickness and a New Index Using a Neural Network.

The optimal relationship between BMO-MRW and pRNFLT was revealed using the broken-stick model. Considerable BMO-MRW thinning preceded pRNFLT thinning. The neural network significantly improved diagnostic power by combining BMO-MRW and pRNFLT.

Reproducibility of Bruch Membrane Opening-Minimum Rim Width Measurements With Spectral Domain Optical Coherence Tomography.

The Spectralis SD-OCT showed excellent reproducibility in BMO-MRW measurements in both normal and glaucoma subjects. The measurements variability was worse in more advanced glaucoma.

Visual Field Inference From Optical Coherence Tomography Using Deep Learning Algorithms: A Comparison Between Devices.

Our deep learning model estimated the VF 24-2 better with a wide field image of SS-OCT than did with retinal nerve fiber layer and ganglion cell-inner plexiform layer images of SD-OCT.

Macular Vessel Density and Ganglion Cell/Inner Plexiform Layer Thickness and Their Combinational Index Using Artificial Intelligence.

Macular vessel density was significantly decreased in glaucoma patients and showed an almost linear correlation with macular GCIPLT.

Deep learning-based prediction of 24-2 visual field from fundus photographs in glaucoma.