Development of Deep Learning Models to Screen Posterior Staphylomas in Highly Myopic Eyes Using UWF-OCT Images.

ABSTRACT:

Purpose

To develop a deep learning (DL) model for screening posterior staphylomas in highly myopic patients using ultra-widefield optical coherence tomography (UWF-OCT) images.

Methods

Our retrospective single-center study collected 1428 qualified UWF-OCT images from 438 highly myopic patients between 2017 and 2019 for model development. An independent test dataset for internal validation included 216 images from 69 highly myopic patients obtained between June 2020 and December 2020. Posterior staphylomas were detected by identifying the staphyloma edges. Seven independent architectures (VGG16, VGG19, ResNet18, ResNet50, ResNet101, DenseNet121, and DenseNet161) were used to train the models and identify staphyloma edges. The area under the receiver operating characteristic (

SUBMITTER: Wang Y 

PROVIDER: S-EPMC12169481 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature