Automatic Determination of Endothelial Cell Density From Donor Cornea Endothelial Cell Images.

ABSTRACT:

Purpose

To determine endothelial cell density (ECD) from real-world donor cornea endothelial cell (EC) images using a self-supervised deep learning segmentation model.

Methods

Two eye banks (Eversight, VisionGift) provided 15,138 single, unique EC images from 8169 donors along with their demographics, tissue characteristics, and ECD. This dataset was utilized for self-supervised training and deep learning inference. The Cornea Image Analysis Reading Center (CIARC) provided a second dataset of 174 donor EC images based on image and tissue quality. These images were used to train a supervised deep learning cell border segmentation model. Evaluation between manual and automated determination of ECD was restricted to the 1939 test EC images with at least 100 cells counted by bot

SUBMITTER: Benetz BAM 

PROVIDER: S-EPMC11346145 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature