Individualized Glaucoma Change Detection Using Deep Learning Auto Encoder-Based Regions of Interest.
Journal:
Translational vision science & technology
Published Date:
Jul 1, 2021
Abstract
PURPOSE: To compare change over time in eye-specific optical coherence tomography (OCT) retinal nerve fiber layer (RNFL)-based region-of-interest (ROI) maps developed using unsupervised deep-learning auto-encoders (DL-AE) to circumpapillary RNFL (cpRNFL) thickness for the detection of glaucomatous progression.