RetinalVasNet: a deep learning approach for robust retinal microvasculature detection.

ABSTRACT:

Introduction

The retinal microvasculature has been definitively linked to a variety of diseases, such as ophthalmological, cardiovascular, and other medical conditions. Precisely identifying the retinal microvasculature is crucial for early detection and monitoring of these diseases. While the majority of existing neural network-based research has primarily focused on utilizing the green channel of fundus images for vessel segmentation, it is important to acknowledge the potential value of other channels in this process.

Methods

This study introduces RetinalVasNet, a new method aimed at enhancing the accuracy and effectiveness of retinal vascular segmentation by implementing a sophisticated neural network architecture and incorporating multi-channel fundus images.

Results

SUBMITTER: Yao Z 

PROVIDER: S-EPMC12390797 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature