Bridging the resources gap: deep learning for fluorescein angiography and optical coherence tomography macular thickness map image translation.

ABSTRACT:

Background

To assess the ability of the pix2pix generative adversarial network (pix2pix GAN) to synthesize clinically useful optical coherence tomography (OCT) color-coded macular thickness maps based on a modest-sized original fluorescein angiography (FA) dataset and the reverse, to be used as a plausible alternative to either imaging technique in patients with diabetic macular edema (DME).

Methods

Original images of 1,195 eyes of 708 nonconsecutive diabetic patients with or without DME were retrospectively analyzed. OCT macular thickness maps and corresponding FA images were preprocessed for use in training and testing the proposed pix2pix GAN. The best quality synthesized images using the test set were selected based on the Fréchet inception distance score, and their qual

SUBMITTER: Abdelmotaal H 

PROVIDER: S-EPMC9434904 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature