Estimation of foveal avascular zone area from a B-scan OCT image using machine learning algorithms.

ABSTRACT:

Purpose

The objective of this study is to estimate the area of the Foveal Avascular Zone (FAZ) from B-scan OCT images using machine learning algorithms.

Methods

We developed machine learning models to predict the FAZ area from OCT B-scan images of eyes without retinal vascular diseases. The study involved three models: Model 1 predicted the FAZ length from B-scan images; Model 2 estimated the FAZ area from the predicted length using 1, 3, or 5 horizontal measurements; and Model 3 converted the FAZ area from pixels to mm2. The models' performance was evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), and the Coefficient of Determination (R2). The FAZ area was subsequently estimated by sequentially applying Models 1→2→3 on a new dataset.

Results

Model

SUBMITTER: Toyama T 

PROVIDER: S-EPMC11649111 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature