Diffusion model based OCT to OCTA translation.

ABSTRACT:

Introduction

This study introduces a conditional diffusion-based approach (Brown Bridge diffusion model, BBDM) for translating optical coherence tomography (OCT) images into OCT Angiography (OCTA).

Methods

Traditional generative adversarial networks (GANs) often face limitations in generalization and structural fidelity due to adversarial loss and one-to-one mappings. In contrast, BBDM employs a bidirectional stochastic process that transitions directly between OCT and OCTA without intermediate conditioning, improving robustness, generalizability and structural consistency. The model was implemented in the latent space of VQGAN, trained on the OCT500 dataset and evaluated on an independent clinical dataset from the University of Illinois at Chicago (UIC) comprising diabetic

SUBMITTER: Badhon RH 

PROVIDER: S-EPMC12698582 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature