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Deep learning for detecting visually impaired cataracts using fundus images.

He Xie¹, Zhongwen Li², Chengchao Wu³

¹National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China.

Frontiers in Cell and Developmental Biology

|August 14, 2023

Summary

This summary is machine-generated.

A new deep learning system (DLS) effectively screens for visually impaired cataracts using fundus images. This AI tool shows potential for early detection and timely referral, outperforming specialists in some cases.

Keywords:

artificial intelligence cataracts deep learning fundus images visual impairment

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Area of Science:

Ophthalmology
Artificial Intelligence
Medical Imaging

Background:

Cataracts are a leading cause of visual impairment globally.
Early detection and screening are crucial for timely intervention and preventing vision loss.
Current screening methods may not always identify visually impaired cataracts effectively.

Purpose of the Study:

To develop and evaluate a deep learning system (DLS) for screening visually impaired cataracts using fundus images.
To classify images into non-cataracts, mild cataracts, and visually impaired cataracts.
To assess the DLS's performance against cataract specialists.

Main Methods:

Utilized 8,395 fundus images from 5,245 subjects across three clinical centers.
Trained and compared three deep learning algorithms: DenseNet121, Inception V3, and ResNet50.
Evaluated system performance using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity.

Main Results:

The DenseNet121 algorithm achieved high AUC values, ranging from 0.938 to 0.999 across internal and external test datasets.
The DLS demonstrated superior performance in detecting visually impaired cataracts compared to cataract specialists (p < 0.05).
The system showed excellent accuracy in classifying cataract severity.

Conclusions:

A function-focused DLS utilizing fundus images shows significant potential for identifying visually impaired cataracts.
This AI-driven screening tool can facilitate timely patient referral to specialized eye care.
The DLS offers a promising approach for improving cataract screening efficiency and effectiveness.