bumbledeep/eyepacs

Dataset Card for Dataset Name

All the images of the dataset come from this kaggle dataset. Some minor modifications have been made to the metadata. All credit goes to the original authors and the contributor on Kaggle.

Dataset Details

Dataset Description

The EyePACS dataset consists of retinal images originally published in the Kaggle competition "Diabetic Retinopathy Detection". This version includes a subset of the original data, specifically the publicly available training images.

• Funded by: California Healthcare Foundation
• Shared by: ilovescience
• License: MIT

Dataset Sources

Retinal images were provided by EyePACS, a free platform for retinopathy screening.

• Repository:
  • kaggle dataset
  • Original location (full dataset)

Uses

Direct Use

Diabetic retinopathy classification (binary or multiclass). Feature extraction (unsupervised or self supervised learning).

Out-of-Scope Use

[More Information Needed]

Dataset Structure

There are no predefined partitions in this dataset; it is up to the user to decide how to split the data.

Dataset Creation

Curation Rationale

Resizing: The images were resized to 1024x1024 if their dimensions exceeded this size; otherwise, they remain unchanged.

Cropping: The black space around the fundus images was cropped by identifying the center and radius of the circle. Some images were either entirely black or almost fully black, with no mask detected. These images were manually removed. However, there may still be some noisy images left.

For more detailed information, see the description of the kaggle dataset.

Source Data

Data Collection and Processing

The images in the dataset come from different models and types of cameras, which can affect the visual appearance of left vs. right. Some images are shown as one would see the retina anatomically (macula on the left, optic nerve on the right for the right eye). Others are shown as one would see through a microscope condensing lens (i.e. inverted, as one sees in a typical live eye exam).

Who are the source data producers?

• EyePACS, the platform that provided the retinal images.
• Emma Dugas, Jared, Jorge, and Will Cukierski, the creators of the kaggle competition and the dataset.

Annotation process

A clinician has rated the presence of diabetic retinopathy in each image on a scale of 0 to 4, according to the following scale:

0 - No DR

1 - Mild

2 - Moderate

3 - Severe

4 - Proliferative DR

Personal and Sensitive Information

[More Information Needed]

Bias, Risks, and Limitations

This dataset contains only the resized and cropped images from kaggle, not the original files.

Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation

Emma Dugas, Jared, Jorge, and Will Cukierski. Diabetic Retinopathy Detection. https://kaggle.com/competitions/diabetic-retinopathy-detection, 2015. Kaggle.

Glossary

[More Information Needed]

Dataset Card Authors

bumbledeep