Using Deep Learning to Automate Goldmann Applanation Tonometry Readings.

ABSTRACT:

Purpose

To develop an objective and automated method for measuring intraocular pressure using deep learning and fixed-force Goldmann applanation tonometry (GAT) techniques.

Design

Prospective cross-sectional study.

Participants

Patients from an academic glaucoma practice.

Methods

Intraocular pressure was estimated by analyzing videos recorded using a standard slit-lamp microscope and fixed-force GAT. Video frames were labeled to identify the outline of the reference tonometer and the applanation mires. A deep learning model was trained to localize and segment the tonometer and mires. Intraocular pressure values were calculated from the deep learning-predicted tonometer and mire diameters using the Imbert-Fick formula. A separate test set was collected prospecti

SUBMITTER: Spaide T 

PROVIDER: S-EPMC7606368 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature