Deep Learning Analysis of Widefield Cornea Endothelial Imaging in Fuchs Dystrophy.

ABSTRACT:

Purpose

To evaluate the use of a deep learning network (DLN) in analyzing widefield specular microscopy (WFSM) images in eyes with Fuchs endothelial corneal dystrophy (FECD).

Design

Cross-sectional clinical observational study.

Participants

A total of 1839 images were obtained via WFSM imaging (CEM-530, Nidek Co Ltd) performed on 155 FECD eyes. A separate data set comprising images from 50 FECD eyes and 50 control eyes (70% training, 30% validation) was used for DLN training, which was tested on 354 images from 55 eyes from varying regions (central, paracentral, and peripheral).

Methods

Images were graded based on a standardized quality score. Central images were compared with paracentral and peripheral images in terms of quality and morphometric parameters: en

SUBMITTER: Tey KY 

PROVIDER: S-EPMC12548096 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature