It is our goal to improve accessibility to quality datasets. To this end, we are organizing big data competitions to collect clinical data in the real-world setting. Previous and upcoming competitions cover topics of interest that include:
- Report Generation from Fundus Fluorescein Angiography Images (2023)
- Prediction of Anti-VEGF Treatment Outcomes in Patients with Diabetic Maculopathies (2021)
- Detection of Diabetic Retinopathy (2019)
Resources
2023 Datasets: Report Generation from Fundus Fluorescein Angiography Images
This dataset comprises over 50,000 FFA images collected in hospital settings for identification of different vascular lesions, anomalies, blood flow patterns and for medical report generation.
2021 Datasets: Prediction of Anti-VEGF Treatment Outcomes
This dataset comprises tens of thousands of OCT images of 2,000 patients before and after receiving loading anti-VEGF treatments, which are a group of medicines that reduce new blood vessel growth or swelling and can be used to treat a number of eye conditions that cause neovascularization or edema under the macular area of the retina at the back eyes.
2019 Datasets: Detection of Diabetic Retinopathy
This dataset consists of more than 50,000 fundus photos captured among people living in rural areas and annotated by highly trained doctors. Images and labels of 3,662 eyes were used for training and another 1,928 eyes were used for testing.
Contribute
You are cordially invited to share your resources with the research community. Incentives to share include:
- Life APTOS membership;
- Improving the discoverability of your work through increased citations;
- Creating opportunities for collaboration;
- Facilitating reuse of your data and software to maximize impact;
- Encouraging higher-quality, transparent research.
Before submitting your work, please review our author guidelines.
