Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning.

ABSTRACT:

Purpose

Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL).

Methods

This study included 1121 OCT volume scans and 10-2 VFs from 289 eyes (257 patients). Macular scans were used to estimate 10-2 VF mean deviation (MD), threshold sensitivities (TS), and total deviation (TD) values at 68 locations. A three-dimensional (3D) convolutional neural network based on the 3D DenseNet121 architecture was used for prediction. We compared DL predictions to those from baseline linear models. We carried out 10-fold stratified cross-validation to optimize generalizability. The performance of the DL and baseline models was compared based on correlations between ground truth and predicted VF m

SUBMITTER: Mohammadzadeh V 

PROVIDER: S-EPMC10627306 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature