Dual contrastive learning for synthesizing unpaired fundus fluorescein angiography from retinal fundus images.

ABSTRACT:

Background

Fundus fluorescein angiography (FFA) is an imaging method used to assess retinal vascular structures by injecting exogenous dye. FFA images provide complementary information to that provided by the widely used color fundus (CF) images. However, the injected dye can cause some adverse side effects, and the method is not suitable for all patients.

Methods

To meet the demand for high-quality FFA images in the diagnosis of retinopathy without side effects to patients, this study proposed an unsupervised image synthesis framework based on dual contrastive learning that can synthesize FFA images from unpaired CF images by inferring the effective mappings and avoid the shortcoming of generating blurred pathological features caused by cycle-consistency in conventional app

SUBMITTER: Zhao J 

PROVIDER: S-EPMC10963839 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature