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Related Experiment Video

Updated: Sep 5, 2025

Quantification of Vascular Parameters in Whole Mount Retinas of Mice with Non-Proliferative and Proliferative Retinopathies

Quantification of Vascular Parameters in Whole Mount Retinas of Mice with Non-Proliferative and Proliferative Retinopathies

Published on: March 12, 2022

The RETA Benchmark for Retinal Vascular Tree Analysis.

Xingzheng Lyu¹, Li Cheng², Sanyuan Zhang³

¹College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China. frankly@zju.edu.cn.

Scientific Data

|July 11, 2022

Summary

This summary is machine-generated.

A new dataset, RETA, with 81 labeled retinal vessel masks aids disease detection. This benchmark facilitates improved automated retinal vessel segmentation and analysis, enhancing clinical applications.

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Last Updated: Sep 5, 2025

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Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

Published on: March 26, 2020

Area of Science:

Ophthalmology
Medical Imaging
Computer Vision

Background:

Retinal blood vessel analysis is crucial for detecting diseases.
Automated segmentation and vascular tree analysis models need robust generalization for clinical use.

Purpose of the Study:

To construct a novel benchmark dataset (RETA) for retinal vessel analysis.
To facilitate the development and evaluation of automated vessel segmentation and analysis algorithms.

Main Methods:

Developed a semi-automated coarse-to-fine workflow for vessel annotation.
Employed multi-stage annotation and label disambiguation with dedicated software to minimize variability.
Collected diverse annotations: binary masks, artery/vein masks, skeletons, bifurcations, trees, and abnormalities.

Main Results:

Constructed the RETA benchmark with 81 high-quality labeled vessel masks.
Achieved significantly improved annotation quality compared to existing open datasets through rigorous validation.
Made the annotation software publicly available for pixel-level vessel visualization.

Conclusions:

The RETA dataset provides a valuable resource for advancing retinal vessel segmentation and analysis.
This benchmark can promote research in cross-modality tubular structure segmentation and analysis.
Improved automated models using RETA could lead to cost-effective disease detection.