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Updated: Jun 20, 2026

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Computational Quantification of Mouse Retinal Vasculature Using ImageJ.

Michel Nader¹, Hirad A Feridooni², Mahtab Tavasoli²

¹Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.

|June 19, 2026

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This summary is machine-generated.

This study presents a standardized ImageJ protocol for analyzing mouse retinal vasculature, enabling reproducible, multi-parameter quantification crucial for studying retinal vascular diseases and evaluating therapies.

Area of Science:

Ophthalmology
Developmental Biology
Medical Imaging

Background:

Mouse retinal vascular development serves as a model for retinal vascular diseases like familial exudative vitreoretinopathy (FEVR).
Current methods for assessing retinal vasculature in mouse models lack standardization and comprehensive analysis, hindering comparative studies.
Phenotypic variability in genetic models necessitates robust, multi-parameter quantification for accurate evaluation.

Purpose of the Study:

To develop and validate a standardized, cost-effective morphometric protocol for quantitative analysis of mouse retinal vasculature.
To enable reproducible, multi-parameter characterization of retinal vascular phenotypes across diverse mouse models.
To facilitate rapid screening of therapeutic interventions for retinal vascular diseases.

Keywords:

Candidate treatments Disease models FIJI Fractal analysis Image analysis Image processing ImageJ Mice Morphometry Retina Screening tool Vessels

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Main Methods:

A standardized ImageJ-based protocol was developed for analyzing mouse retinal vasculature in flat mounts.
The protocol involves measuring vascular disorganization, total vascular and retinal area, and cell clusters.
Image processing, binarization, skeletonization, and quantification of vascular density, branching, junctions, and fractal dimensions were performed.

Main Results:

The protocol provides reproducible, quantitative measurements of multiple vascular features, including density, branching, and fractal properties.
It effectively captures phenotypic variability across different mouse models.
The workflow is optimized for rapid and cost-effective screening of vascular outcomes.

Conclusions:

This ImageJ-based protocol offers a standardized, comprehensive framework for analyzing mouse retinal vasculature.
It is suitable for comparative studies and high-throughput screening of therapeutic interventions in retinal vascular diseases.
The method enhances the reproducibility and efficiency of retinal vascular research.