Diagnosis of Choroidal Disease With Deep Learning-Based Image Enhancement and Volumetric Quantification of Optical Coherence Tomography.

ABSTRACT:

Purpose

The purpose of this study was to quantify choroidal vessels (CVs) in pathological eyes in three dimensions (3D) using optical coherence tomography (OCT) and a deep-learning analysis.

Methods

A single-center retrospective study including 34 eyes of 34 patients (7 women and 27 men) with treatment-naïve central serous chorioretinopathy (CSC) and 33 eyes of 17 patients (7 women and 10 men) with Vogt-Koyanagi-Harada disease (VKH) or sympathetic ophthalmitis (SO) were imaged consecutively between October 2012 and May 2019 with a swept source OCT. Seventy-seven eyes of 39 age-matched volunteers (26 women and 13 men) with no sign of ocular pathology were imaged for comparison. Deep-learning-based image enhancement pipeline enabled CV segmentation and visualization in 3D, aft

SUBMITTER: Maruyama K 

PROVIDER: S-EPMC8762713 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature