Automated Deep Learning Quantification of Avascular Area and Intravitreal Neovascularization in Retinal…

Animal / preclinicalTranslational vision science & technology· Jun 2026

Automated Deep Learning Quantification of Avascular Area and Intravitreal Neovascularization in Retinal Flatmounts of Rodent Oxygen-Induced Retinopathy Models.

Neal S Shah, Aniket Ramshekar, Bright Asare-Bediako … M Elizabeth Hartnett

RetinaAnimal / preclinicalQ1IF 2.8

Reviewers preferred the AI model's neovascularization outlines in most comparisons

Automated Deep Learning Quantification of Avascular Area and Intravitreal Neovascularization in Retinal Flatmounts of Rodent Oxygen-Induced Retinopathy Models.

Neal S Shah … M Elizabeth Hartnett

Translational vision science & technology · Jun 2026 · Q1 in Ophthalmology

Purpose

To develop a single deep learning model that quantifies the retinal avascular area (avascular area) and intravitreal neovascularization (intravitreal neovascularization) in rodent oxygen-induced retinopathy (oxygen-induced retinopathy) models.

Methods

We assessed intergrader reliability and agreement at metric and pixel levels.

n = 325 images

83.3%

Results

83.3%

Human reviewers picked the deep-learning model's abnormal blood vessel outline as best in 83.3% of comparisons.

n = 325 images

More results

Intergrader reliability was high for percent avascular area (mouse intraclass correlation coefficient [ICC] = 0.840; rat ICC = 0.971), moderate for rat percent intravitreal neovascularization (ICC = 0.509), and low for mouse percent intravitreal neovascularization (ICC = -0.082).

More results

Metric-level correlation was strong in rat oxygen-induced retinopathy (percent avascular area r = 0.979; percent intravitreal neovascularization r = 0.943) and for mouse percent avascular area (r = 0.957), but weak for mouse percent intravitreal neovascularization (r = 0.265).

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Conclusion

Our deep learning model supports automated rat oxygen-induced retinopathy analysis while maintaining mouse performance and may improve reproducibility of oxygen-induced retinopathy measurements.

Automated Deep Learning Quantification of Avascular Area and Intravitreal Neovascularization in Retinal Flatmounts of Rodent Oxygen-Induced Retinopathy Models.

Automated Deep Learning Quantification of Avascular Area and Intravitreal Neovascularization in Retinal Flatmounts of Rodent Oxygen-Induced Retinopathy Models.

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