A foundation model for universal 3D blood vessel segmentation. Paper accepted @ CVPR25.

Official website of our paper: Applications of Deep Learning in Fundus Images: A Review. Newly-released datasets and recently-published papers will be updated regularly.

A synthesis pipeline for annotation-free blood vessel segmentation in cerebral 3D OCTA images. Paper accepted @ MICCAI24.

Checkpoints to reproduce results for the paper "IterMiUnet: A lightweight architecture for automatic blood vessel segmentation" accepted in Multimedia Tools and Applications 2023

SeqSeg (Sequential Segmentations)

Blood vessel segmentation for retina and eggs.

This DR detection methodology has six steps: preprocessing, segmentation of blood vessels, segmentation of OD, detection of MAs and hemorrhages, feature extraction and classification. For segmentation of blood vessels BCDU-Net is used. For OD segmentation, U-Net model is used. MAs and hemorrhages are extracted using Otsu thresholding technique. …

Segmentation of blood vessels in fundus photography images

Converts blood vessels in retinal images to binarized segmentation

The repository contains the MATLAB script. The .csv file in the Results folder is used as ground truth for the study of the proposed algorithm.

This project focuses on segmenting retinal blood vessels from fundus images using a U Net based deep learning model. The goal is to build a simple, clear, and reproducible pipeline that loads the dataset, pairs images with their masks, trains a U Net, evaluates the model, and visualizes the predicted segmentation maps.

Blood Vessel Segmentation was done on Messidor Dataset. Using the weights of a model which was trained on Drive2004 Dataset and ChaseDB

This is a project of blood vessel segmentation using fuzzy logic method.

An app to calculate and visualize blood vessel diameter and area as functions of time, given .tif, .lif, or .mat files

Blood Vessel Segmentation of Diabetic Retinopathy Fundus Image