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Related Experiment Video

Updated: Oct 17, 2025

$Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter$

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Deep learning for predicting uncorrected refractive error using posterior segment optical coherence tomography

Tae Keun Yoo^1,2,3, Ik Hee Ryu^4,5, Jin Kuk Kim^4,5

¹B&VIIT Eye Center, Seoul, South Korea. eyetaekeunyoo@gmail.com.

Eye (London, England)

|October 6, 2021

Summary

This summary is machine-generated.

A deep learning model uses optical coherence tomography (OCT) images to estimate refractive error, showing potential for clinical use in detecting high myopia and preventing overlooked risks.

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Application of Optical Coherence Tomography to a Mouse Model of Retinopathy

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Published on: January 12, 2022

Area of Science:

Ophthalmology
Medical Imaging
Artificial Intelligence

Background:

Refractive error estimation is crucial for eye health.
Current methods may not always capture subtle changes.
Optical coherence tomography (OCT) offers detailed posterior segment imaging.

Purpose of the Study:

To evaluate a deep learning model for estimating uncorrected refractive error.
To assess the model's ability to detect high myopia using OCT images.
To explore the potential of OCT as an imaging modality for refractive error assessment.

Main Methods:

A retrospective study with development and test datasets.
A deep learning regression model (ResNet50) trained on horizontal OCT images to predict spherical equivalent (SE).
Evaluation of the model for high myopia detection and visualization of features using saliency maps (Grad-CAM).

Main Results:

The model achieved a low mean absolute error (2.66 D) for SE prediction.
A significant Pearson correlation coefficient (0.588) was observed in the test dataset.
The model demonstrated an area under the ROC curve of 0.813 for high myopia detection with 71.4% accuracy.

Conclusions:

Deep learning algorithms can estimate refractive error from OCT images.
This approach may aid clinicians in identifying refractive error risks during OCT assessments.
OCT shows promise as an imaging modality for refractive error evaluation.