Evaluation of a computer-aided diagnostic model for corneal diseases by analyzing in vivo confocal microscopy images.

ABSTRACT:

Objective

In order to automatically and rapidly recognize the layers of corneal images using in vivo confocal microscopy (IVCM) and classify them into normal and abnormal images, a computer-aided diagnostic model was developed and tested based on deep learning to reduce physicians' workload.

Methods

A total of 19,612 corneal images were retrospectively collected from 423 patients who underwent IVCM between January 2021 and August 2022 from Renmin Hospital of Wuhan University (Wuhan, China) and Zhongnan Hospital of Wuhan University (Wuhan, China). Images were then reviewed and categorized by three corneal specialists before training and testing the models, including the layer recognition model (epithelium, bowman's membrane, stroma, and endothelium) and diagnostic mode

SUBMITTER: Yan Y 

PROVIDER: S-EPMC10157182 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature