Glaucoma Dataset: Retinal Fundus Images for Automated Detection

A collection of retinal fundus images for automated glaucoma detection and classification. The dataset contains between 10,000 and 100,000 high-quality images and is organized in the standard imagefolder format. It was authored by Nj-1111 and last updated on 2026-04-18.

Use Cases

• Train image classification models for glaucoma detection based on retinal fundus images.
• Benchmark computer vision algorithms for medical image analysis using the described image collection.
• Develop automated diagnostic tools for ophthalmology based on the high-quality fundus images.

Strengths

• Contains between 10,000 and 100,000 images, suggesting a substantial scale.
• Images are described as high-quality, which is beneficial for model training.
• Uses the standard imagefolder format, which likely simplifies integration with common ML frameworks.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

Nj-1111 on Hugging Face

Collection Method

Collection of retinal fundus images, method unspecified.

Time Range

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Freshness

Last updated 2026-04-18 21:12:51; freshness should be verified.

Geography

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