Deep Learning Detection of Sea Fan Neovascularization From Ultra-Widefield Color Fundus Photographs of Patients With Sickle Cell Hemoglobinopathy.

ABSTRACT:

Importance

Adherence to screening for vision-threatening proliferative sickle cell retinopathy is limited among patients with sickle cell hemoglobinopathy despite guidelines recommending dilated fundus examinations beginning in childhood. An automated algorithm for detecting sea fan neovascularization from ultra-widefield color fundus photographs could expand access to rapid retinal evaluations to identify patients at risk of vision loss from proliferative sickle cell retinopathy.

Objective

To develop a deep learning system for detecting sea fan neovascularization from ultra-widefield color fundus photographs from patients with sickle cell hemoglobinopathy.

Design, setting, and participants

In a cross-sectional study conducted at a single-institution, tertiary academi

SUBMITTER: Cai S 

PROVIDER: S-EPMC7774049 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature