Development of a β-Variational Autoencoder for Disentangled Latent Space Representation of Anterior Segment Optical Coherence Tomography Images.

ABSTRACT:

Purpose

To investigate the feasibility of extracting a low-dimensional latent structure of anterior segment optical coherence tomography (AS-OCT) images by use of a β-variational autoencoder (β-VAE).

Methods

We retrospectively collected 2111 AS-OCT images from 2111 eyes of 1261 participants from the ongoing Asan Glaucoma Progression Study. After hyperparameter optimization, the images were analyzed with β-VAE.

Results

The mean participant age was 64.4 years, with mean values of visual field index and mean deviation of 86.4% and -5.33 dB, respectively. After experiments, a latent space size of 6 and β value of 53 were selected for latent space analysis with β-VAE. Latent variables were successfully disentangled, showing readily interpretable distinct characteristics, s

SUBMITTER: Shon K 

PROVIDER: S-EPMC8842480 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature