Segmentation of Retinal Blood Vessels Using Deep Learning

2023/03/16 by Ifeyinwa Linda Anene, Anene, Ifeyinwa Linda, Yongmin Li +1
Computer Science · Medicine · #Computer Vision and Pattern Recognition (cs.CV) #Digital Imaging for Blood Diseases #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Retinal Imaging and Analysis #Retinal and Optic Conditions #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2303.09679

openalex publication_date 2023/03/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The morphology of retinal blood vessels can indicate various diseases in the human body, and researchers have been working on automatic scanning and segmentation of retinal images to aid diagnosis. This project compares the performance of four neural network architectures in segmenting retinal images, using a combined dataset from different databases, namely the UNet, DR-VNet, UNet-ResNet and UNet-VGG.

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